def test_trial_results():
assert OSPREY_BIN is not None
cwd = os.path.abspath(os.curdir)
dirname = tempfile.mkdtemp()
try:
os.chdir(dirname)
subprocess.check_call([
OSPREY_BIN, 'skeleton', '-t', 'random_example', '-f', 'config.yaml'
])
subprocess.check_call([OSPREY_BIN, 'worker', 'config.yaml', '-n', '5'])
assert os.path.exists('osprey-trials.db')
config = Config('config.yaml')
df = config.trial_results()
assert df.shape[0] == 5
for key in Trial.__table__.columns.keys():
assert key in df.columns
finally:
os.chdir(cwd)
shutil.rmtree(dirname)
def test_trial_results():
assert OSPREY_BIN is not None
cwd = os.path.abspath(os.curdir)
dirname = tempfile.mkdtemp()
try:
os.chdir(dirname)
subprocess.check_call([OSPREY_BIN, 'skeleton', '-t', 'random_example',
'-f', 'config.yaml'])
subprocess.check_call([OSPREY_BIN, 'worker', 'config.yaml', '-n', '5'])
assert os.path.exists('osprey-trials.db')
config = Config('config.yaml')
df = config.trial_results()
assert df.shape[0] == 5
for key in Trial.__table__.columns.keys():
assert key in df.columns
finally:
os.chdir(cwd)
shutil.rmtree(dirname)
# In[4]:
root_dir = 'fs-peptide'
# Load Configuation Files
databases = {
'bayesian': root_dir + '/gp-m52-ei-tica-indv/config-all_tor.yaml',
'random': root_dir + '/rand-tica-indv/config_random-all_tor.yaml',
'sobol': root_dir + '/sobol-tica-indv/config-all_tor.yaml',
'tpe': root_dir + '/tpe-s20-g25-tica-indv/config-all_tor.yaml'
}
all_dfs = []
for k, v in databases.items():
config = Config(v)
df = config.trial_results()
df['method'] = k
all_dfs.append(df)
df_all = pd.concat(all_dfs)
# In[7]:
df_all.head()
# # Drop unnecessary columns and rename
# In[67]:
df = df_all.loc[:, [
'parameters', 'project_name', 'mean_test_score', 'mean_train_score',
if len(argv) != 4:
print('usage: sample_db.py config.yaml sample_size n_samples')
exit(1)
inp_file = argv[1]
num = int(argv[2]) # TOTAL size of samples to use e.g. 100
iter = int(argv[3]) # Number of splits e.g. 5
# This will give 5 splits of 20 samples each.100
if num % iter != 0:
print('sample_size not strictly divisible by n_samples')
exit(1)
# Get original database and history
config1 = Config(inp_file)
df1 = config1.trial_results()
hist1 = config1.trials().query(Trial).all()
# Main loop
for name, group in df1.groupby('project_name'):
# Sample the group
sample = group.sample(num, random_state=42)
cv = KFold(n_splits=iter, random_state=42)
all_keep = sample['id'].values
for i, (_, test_idx) in enumerate(cv.split(all_keep)):
keep = all_keep[test_idx]
db2 = make_session('sqlite:///osprey-trials-{0}-{1}.db'.format(int(num/iter), i), project_name=name)