def main(input_path: str) -> None:
config = Config.get(input_conf=load_json_file(file_path=input_path))
data = load_pickle(file_path=config.data_path)
np.random.seed(seed=config.seed)
results = generate_empty_results_dict()
results['method_names'] = config.method_names
print(f'Input: {asdict(config)}')
print('Run experiments!')
for weights, data_list in data.items():
results_per_weight = list()
print(f'Run experiments for weights: {weights}')
for data in tqdm(data_list):
results_per_weight += [main_experiment(data=data, config=config)]
results['results'][weights] = results_per_weight
date = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
suffix = '_'.join(
['results_agnostic_sample_based', date, f'_{weights}'])
to_pickle(output_dir=config.output_dir,
data=results_per_weight,
suffix=suffix)
date = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
pattern_type = f'pattern_type_{extract_pattern_type(data_path=config.data_path)}'
suffix = '_'.join(['results_agnostic_sample_based', date, pattern_type])
to_pickle(output_dir=config.output_dir, data=results, suffix=suffix)
def main(input_path: str) -> None:
config = Config.get(input_conf=load_json_file(file_path=input_path))
print(f'Input: {asdict(config)}')
for type_of_experiment in config.experiment_types:
print(f'Type of experiment: {type_of_experiment}.')
for type_of_signal in config.signal_types:
print(f'Type of signal: {type_of_signal}.')
data = create_datasets(config=config,
signal_type=type_of_signal,
experiment_type=type_of_experiment)
date = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
pattern_type = f'pattern_type_{config.pattern_type}'
suffix = '_'.join(
[type_of_experiment, type_of_signal, date, pattern_type])
to_pickle(output_dir=config.output_dir, data=data, suffix=suffix)
def main(config_path: str):
config = Config.get(input_conf=load_json_file(file_path=config_path))
paths_evaluation_results = evaluate(config=config)
plot(config=config, score_paths=paths_evaluation_results)
print('Save results!')
output_paths = list()
date = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
pattern_type = f'pattern_type_{extract_pattern_type(data_path=config.data_path)}'
suffix = '_'.join(['evaluation', date, pattern_type])
output_paths += [
to_pickle(output_dir=config.output_dir_scores,
data=scores,
suffix=suffix)
]
return output_paths
def get_command_line_arguments() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument('--path',
dest='path',
required=True,
help='Input file path of json file containing'
'input parameter for the experiment!')
return parser.parse_args()
if __name__ == '__main__':
args = get_command_line_arguments()
try:
evaluate(config=Config.get(input_conf=load_json_file(
file_path=args.path)))
except KeyboardInterrupt as e:
print(e)
def setUp(self):
self.tol = 1e-23
self.Fe78_res_dict = load_json_file(resolve_resource("pyisocalc", "single_pattern", "Fe78"))
}),
'H': SimpleMock({
'get_segments': lambda: [SegmentStub(element_stubs['H'], 1)],
'charge': lambda: 1
}),
'Fe100H89O10': SimpleMock({
'get_segments': lambda: [SegmentStub(element_stubs['Fe'], 100), SegmentStub(element_stubs['H'], 89),
SegmentStub(element_stubs['O'], 10)],
'charge': lambda: 369
})
}
chemcalc_ref_values = {}
for sf_str in sf_stubs:
fn = resolve_resource("pyisocalc", "perfect_pattern", sf_str)
res_dict = load_json_file(fn)
chemcalc_ref_values[sf_str] = res_dict
class ElementTest(unittest.TestCase):
def test_init(self):
valid_args = ('H', 'Ar', 1, 49)
valueerror_args = ('', 'foo', -45, 2345)
typeerror_args = (1.0, None)
for arg in valid_args:
Element(arg)
for arg in valueerror_args:
self.assertRaises(ValueError, Element, arg)
for arg in typeerror_args:
self.assertRaises(TypeError, Element, arg)
import base64
import utils
import common
import os
if __name__ == "__main__":
CWD = os.path.dirname(os.path.realpath(__file__))
config = common.load_json_file(CWD + "/config.json")
""" the password / ipv4 encrypted base64.b64encode("PASS")
import base64
print base64.b64encode()
print base64.b64decode("cGFzc3dvcmQ=")
"""
with utils.SSH(base64.b64decode(config["SSH"]['IP_ADDRESS']),
the_user=base64.b64decode(config["SSH"]['THE_USER']),
the_password=base64.b64decode(config["SSH"]['THE_PASSWORD'])
) as ssh:
cloud = common.UnderCloud(config=config)
cloud.copy_from_workspace(ssh, local_dest_dir=CWD,
local_file="tempest_cleanup.sh",
remote_file="/home/stack/tempest_cleanup.sh",
chown="stack:stack")
ssh.send_cmd("sudo /home/stack/tempest_cleanup.sh", ignore_exit=True)
# copy private key to workspace
cloud.copy_to_workspace(ssh, local_dest_dir=CWD, local_file="id_rsa.tar.gz",
remote_file="/home/stack/.ssh/id_rsa")
cloud.get_undercloud_nodes(ssh)
cloud.show_overcloud_nodes()
cloud.get_overcloud_status(ssh)
# cleanup logs on all machines
('precision_based_scores', 'max_precision'),
# ('precision_based_scores', 'avg_precision')
])
print(f'Create heat maps!')
pattern_type = int(extract_pattern_type(data_path=config.data_path))
global_heat_maps(scores=scores, config=config, rnd_experiment_idx=idx,
pattern_type=pattern_type, snrs_of_interest=['0.00', '0.04', '0.08'])
sample_based_heat_maps(scores=scores, config=config, data=data_dict,
rnd_sample_idx=rnd_sample_idx, pattern_type=pattern_type,
snrs_of_interest=['0.00', '0.04', '0.08'])
def get_command_line_arguments() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument('--path', dest='path', required=True,
help='Input file path of json file containing'
'input parameter for the experiment!')
return parser.parse_args()
if __name__ == '__main__':
args = get_command_line_arguments()
path = args.path
try:
c = Config.get(input_conf=load_json_file(file_path=path))
input_paths = ['results/scores/data_evaluation_2021-04-30-12-32-54_pattern_type_0.pkl']
plot(config=c, score_paths=input_paths)
except KeyboardInterrupt as e:
print(e)
