def _setup_directories(config):
file_util.makedirs(config['results_dir'])
with file_util.open(
os.path.join(config['results_dir'],
config['experiment_name'] + '_info.txt'),
'w') as outfile:
outfile.write(fg_core.to_json(config))
def _setup_directories(config):
try:
file_util.makedirs(config['results_dir'])
file_util.makedirs('./runs/{}'.format(config['experiment_name']))
except FileExistsError:
pass
with file_util.open(
os.path.join(config['results_dir'],
config['experiment_name'] + '_info.txt'),
'w') as outfile:
outfile.write(fg_core.to_json(config))
def write_csv_output(dataframes, directory):
"""Write csv file outputs."""
movies, users, ratings = dataframes
file_util.makedirs(directory)
del movies['tag_id'] # This column isn't necessary.
users.to_csv(file_util.open(os.path.join(directory, 'users.csv'), 'w'),
index=False,
columns=['userId'])
movies.to_csv(file_util.open(os.path.join(directory, 'movies.csv'), 'w'),
index=False)
ratings.to_csv(file_util.open(os.path.join(directory, 'ratings.csv'), 'w'),
index=False)
def write_csv_output(dataframe, filename, directory):
"""Write dataframe to CSV.
Args:
dataframe: pandas DataFrame
filename: name of the file (should end in ".csv")
directory: directory to write to
"""
if not filename.endswith('.csv'):
raise ValueError('Filename does not end in .csv')
file_util.makedirs(directory)
dataframe.to_csv(file_util.open(os.path.join(directory, filename), 'w'),
index=False)
def main(argv):
if len(argv) > 1:
raise app.UsageError('Too many command-line arguments.')
plotting_dir = os.path.join(FLAGS.plotting_dir, '%d' % FLAGS.seed)
file_util.makedirs(plotting_dir)
lending_plots.plot_steady_state_distribution(plotting_dir)
experiment_fn = functools.partial(
lending.Experiment,
cluster_probabilities=DELAYED_IMPACT_CLUSTER_PROBS,
group_0_prob=0.5,
interest_rate=1.0,
bank_starting_cash=10000,
seed=FLAGS.seed,
num_steps=FLAGS.num_steps,
# No need for burn in since the agent is an oracle agent.
burnin=1,
cluster_shift_increment=FLAGS.cluster_shift_increment,
include_cumulative_loans=True,
return_json=False)
logging.info(
'experiment params %s %s',
experiment_fn(threshold_policy=lending.EQUALIZE_OPPORTUNITY).asdict(),
experiment_fn(threshold_policy=lending.MAXIMIZE_REWARD).asdict())
env, agent = experiment_fn(
threshold_policy=lending.EQUALIZE_OPPORTUNITY).scenario_builder()
logging.info('environment params %s', env.initial_params.asdict())
logging.info('agent params %s', agent.params.asdict())
# Run two long-running experiments and then use the results for all further
# plotting.
equality_of_opportunity_result = experiment_fn(
threshold_policy=lending.EQUALIZE_OPPORTUNITY).run()
# The static experiment removes the delayed effects of defaulting on future
# credit scores.
static_equality_of_opportunity_result = experiment_fn(
threshold_policy=lending.EQUALIZE_OPPORTUNITY,
cluster_shift_increment=0).run()
maximize_reward_result = experiment_fn(
threshold_policy=lending.MAXIMIZE_REWARD).run()
lending_plots.do_plotting(
maximize_reward_result,
equality_of_opportunity_result,
static_equality_of_opportunity_result,
plotting_dir,
options=ACM_FAT_2020_PLOTS)
def test_delete_recursively(self):
test_root = self.create_tempdir().full_path
file_util.makedirs('%s/my/favorite/multilevel/directory' % test_root)
file_util.delete_recursively('%s/my/favorite' % test_root)
self.assertTrue(file_util.exists('%s/my' % test_root))
self.assertFalse(file_util.exists('%s/my/favorite' % test_root))
def test_makedirs(self):
test_root = self.create_tempdir().full_path
file_util.makedirs('%s/my/multilevel/directory' % test_root)
self.assertTrue(file_util.exists('%s/my/multilevel/directory' % test_root))
