def download_experiment_to_file(experiment_name, file_path):
if os.path.exists(file_path):
os.unlink(file_path)
file_database = ExperimentDatabaseManager(file=file_path, cache_size=100000)
file_database.set_experiment(experiment_name)
reading_manager = ExperimentDatabaseReadingManager(mysql_credentials=credentials)
query = '''SELECT (table_name) FROM information_schema.columns WHERE column_name = 'experiment_name' AND table_schema = '%s';''' % credentials['database']
data = reading_manager.get_data_from_query(query)
tables = [x[0] for x in data]
tables.remove('experiments')
print("Gotten list of all tables:")
print('\n'.join(tables))
for table in tables:
print("Downloading data from ", table)
table_data = reading_manager.get_data(table, experiment_name)
if table_data is None:
print("No data found in table for this experiment, skipping")
continue
print("Gotten keys", table_data.keys())
for key in table_data.keys():
print('\t%s is %s' % (key, str(type(table_data[key][0]))))
table_data.pop('experiment_name')
file_database.insert_experiment_data(table, table_data)
print("Finishing up writing to file...")
file_database.close()
def test_read_write_4(self):
if os.path.exists('sample.db'):
os.unlink('sample.db')
database_manager = ExperimentDatabaseManager(file='sample.db',
cache_size=40)
database_manager.delete_experiment(
'writing_numerical_data_test_case_4')
database_manager.set_experiment('writing_numerical_data_test_case_4')
inserted_data = dict()
inserted_data['var_1'] = 19
inserted_data['var_2'] = 109
inserted_data['var_3'] = np.nan
database_manager.insert_experiment_data(
'writing_numerical_data_test_case_4', inserted_data)
database_manager.flush()
database_manager_2 = ExperimentDatabaseReadingManager(file='sample.db')
read_back_data = database_manager_2.get_data(
'writing_numerical_data_test_case_4',
'writing_numerical_data_test_case_4')
assert read_back_data['var_1'][0] == inserted_data[
'var_1'] # Always returns list
assert read_back_data['var_2'][0] == inserted_data[
'var_2'] # Always returns list
assert read_back_data['var_3'][0] == 0 # Always returns list
# Doing it at the end to check if it flushing works properly
database_manager.delete_experiment(
'writing_numerical_data_test_case_4')
database_manager.close()
def test_write_to_network_and_file_and_read_from_both(self):
if os.path.exists('sample.db'):
os.unlink('sample.db')
print("Writing to server")
database_manager = ExperimentDatabaseManager(
mysql_credentials=sql_credentials.credentials,
file='sample.db',
cache_size=40)
database_manager.delete_experiment('database_plots_test_case_1')
database_manager.set_experiment('database_plots_test_case_1')
self.write_to_database(database_manager)
database_manager.close()
download_experiment_to_file(
experiment_name='database_plots_test_case_1',
file_path='output/downloaded_database.db')
print("Reading back from downloaded file")
database_reading_manager = ExperimentDatabaseReadingManager(
file='output/downloaded_database.db')
self.read_from_database(database_reading_manager)
print("Reading back from cache file")
database_reading_manager = ExperimentDatabaseReadingManager(
file='sample.db')
self.read_from_database(database_reading_manager)
database_manager = ExperimentDatabaseManager(
mysql_credentials=sql_credentials.credentials, cache_size=40)
database_manager.delete_experiment('database_plots_test_case_1')
database_manager.close()
def test_read_write_4(self):
database_manager = ExperimentDatabaseManager(
mysql_credentials=sql_credentials.credentials, cache_size=40)
database_manager.delete_experiment(
'writing_numerical_data_test_case_4')
database_manager.set_experiment('writing_numerical_data_test_case_4')
inserted_data = dict()
inserted_data['var_1'] = 19
inserted_data['var_2'] = 109
inserted_data['var_3'] = np.nan
database_manager.insert_experiment_data(
'writing_numerical_data_test_case_4', inserted_data)
database_manager.flush()
database_manager_2 = ExperimentDatabaseReadingManager(
mysql_credentials=sql_credentials.credentials)
read_back_data = database_manager_2.get_data(
'writing_numerical_data_test_case_4',
'writing_numerical_data_test_case_4')
assert read_back_data['var_1'][0] == inserted_data[
'var_1'] # Always returns list
assert read_back_data['var_2'][0] == inserted_data[
'var_2'] # Always returns list
assert read_back_data['var_3'][0] == 0 # Always returns list
# Doing it at the end to check if it flushing works properly
database_manager.delete_experiment(
'writing_numerical_data_test_case_4')
database_manager.close()
def read_from_database(self):
database_reading_manager = ExperimentDatabaseReadingManager(sql_credentials.credentials)
efficiency_plot = General2dBinningPlot(bins=np.array([0, 1, 2, 3, 4]), histogram_log=False,
histogram_fraction=False)
efficiency_plot.read_from_database(database_reading_manager, 'database_plots_test_case_1')
efficiency_plot.draw()
plt.savefig('output/test-reproduced-plot.png')
def test_read_write_3(self):
if os.path.exists('sample.db'):
os.unlink('sample.db')
database_manager = ExperimentDatabaseManager(file='sample.db',
cache_size=40)
database_manager.delete_experiment(
'writing_numerical_data_test_case_3')
database_manager.set_experiment('writing_numerical_data_test_case_3')
inserted_data = dict()
inserted_data['var_1'] = np.array([19, 20])
inserted_data['var_2'] = np.array([109, 110])
inserted_data['var_3'] = np.array([54.1, 43])
inserted_data['var_4'] = np.array(['hello', 'world'])
database_manager.insert_experiment_data(
'writing_numerical_data_test_case_3', inserted_data)
database_manager.flush()
database_manager_2 = ExperimentDatabaseReadingManager(file='sample.db')
read_back_data = database_manager_2.get_data(
'writing_numerical_data_test_case_3',
'writing_numerical_data_test_case_3')
assert read_back_data['var_1'][0] == inserted_data['var_1'][0]
assert read_back_data['var_1'][1] == inserted_data['var_1'][1]
assert read_back_data['var_2'][0] == inserted_data['var_2'][0]
assert read_back_data['var_2'][1] == inserted_data['var_2'][1]
assert read_back_data['var_3'][0] == inserted_data['var_3'][0]
assert read_back_data['var_3'][1] == inserted_data['var_3'][1]
assert read_back_data['var_4'][0] == inserted_data['var_4'][0]
assert read_back_data['var_4'][1] == inserted_data['var_4'][1]
# Doing it at the end to check if it flushing works properly
# database_manager.delete_experiment('writing_numerical_data_test_case_3')
database_manager.close()
def test_read_write_2(self):
database_manager = ExperimentDatabaseManager(
mysql_credentials=sql_credentials.credentials, cache_size=40)
database_manager.delete_experiment(
'writing_numerical_data_test_case_2')
database_manager.set_experiment('writing_numerical_data_test_case_2')
inserted_data = dict()
inserted_data['var_1'] = [19, 20]
inserted_data['var_2'] = [109, 110]
inserted_data['var_3'] = [54.1, 43]
database_manager.insert_experiment_data(
'writing_numerical_data_test_case_2', inserted_data)
database_manager.flush()
database_manager_2 = ExperimentDatabaseReadingManager(
mysql_credentials=sql_credentials.credentials)
read_back_data = database_manager_2.get_data(
'writing_numerical_data_test_case_2',
'writing_numerical_data_test_case_2')
assert read_back_data['var_1'][0] == inserted_data['var_1'][0]
assert read_back_data['var_1'][1] == inserted_data['var_1'][1]
assert read_back_data['var_2'][0] == inserted_data['var_2'][0]
assert read_back_data['var_2'][1] == inserted_data['var_2'][1]
assert read_back_data['var_3'][0] == inserted_data['var_3'][0]
assert read_back_data['var_3'][1] == inserted_data['var_3'][1]
# Doing it at the end to check if it flushing works properly
database_manager.delete_experiment(
'writing_numerical_data_test_case_2')
database_manager.close()
def test_read_write_file(self):
if os.path.exists('sample.db'):
os.unlink('sample.db')
database_manager = ExperimentDatabaseManager(file='sample.db',
cache_size=40)
print("Writing to file")
self.write_to_database(database_manager)
database_manager.close()
print("Reading back from file")
database_reading_manager = ExperimentDatabaseReadingManager(
file='sample.db')
self.read_from_database(database_reading_manager)
if os.path.exists('sample.db'):
os.unlink('sample.db')
def test_read_write(self):
print("Writing to server")
database_manager = ExperimentDatabaseManager(
mysql_credentials=sql_credentials.credentials, cache_size=40)
self.write_to_database(database_manager)
database_manager.close()
print("Reading back from server")
database_reading_manager = ExperimentDatabaseReadingManager(
sql_credentials.credentials)
self.read_from_database(database_reading_manager)
database_manager = ExperimentDatabaseManager(
mysql_credentials=sql_credentials.credentials, cache_size=40)
database_manager.delete_experiment('database_plots_test_case_1')
database_manager.close()
'table_prefix',
help=
'Output directory with .bin.gz files or a txt file with full paths of the bin gz files'
)
parser.add_argument('output', help='PDF file')
parser.add_argument('--condition_string',
default='',
help='Condition sql string')
args = parser.parse_args()
condition_string = None
if len(args.condition_string) != 0:
condition_string = args.condition_string
plotter = HGCalAnalysisPlotter([
'settings', 'efficiency_fo_truth', 'fake_rate_fo_pred',
'response_fo_truth', 'response_fo_pred', 'response_sum_fo_truth',
'energy_resolution'
])
reading_manager = ExperimentDatabaseReadingManager(
mysql_credentials=sql_credentials.credentials)
plotter.add_data_from_database(reading_manager,
table_prefix=args.table_prefix,
condition=condition_string)
# plotter.add_data_from_database(reading_manager, table_prefix='alpha_plots_a2')
# plotter.write_to_pdf(args.output, formatter=lambda x: 'Optimized f1 score\n$\\alpha$ param=$%.2f$ \n$\\beta$ param$=%.2f$ \n$\\beta=%.4f$\n$d=%.4f$\n'%(x['beta_param'],x['alpha_param'],x['beta_threshold'],x['distance_threshold']))
plotter.write_to_pdf(
args.output, formatter=lambda x: 'IOU threshold %f' % x['iou_threshold'])
unique_id_path = os.path.join(train.outputDir, 'unique_id.txt')
if os.path.exists(unique_id_path):
with open(unique_id_path, 'r') as f:
unique_id = f.readlines()[0].strip()
else:
unique_id = str(uuid.uuid4())[:8]
with open(unique_id_path, 'w') as f:
f.write(unique_id + '\n')
nbatch = 50000 #this is rather low, and can be set to a higher values e.g. when training on V100s
database_manager = ExperimentDatabaseManager(file=os.path.join(
train.outputDir, "training_metrics.db"),
cache_size=100)
database_reading_manager = ExperimentDatabaseReadingManager(
file=os.path.join(train.outputDir, "training_metrics.db"))
database_manager.set_experiment(unique_id)
metadata = matching_and_analysis.build_metadeta_dict(
beta_threshold=0.5,
distance_threshold=0.5,
iou_threshold=0.0001,
matching_type=matching_and_analysis.MATCHING_TYPE_MAX_FOUND)
analyzer = matching_and_analysis.OCAnlayzerWrapper(metadata)
cb += [
RunningMetricsDatabaseAdditionCallback(td,
tensorboard_manager,
database_manager=database_manager,
analyzer=analyzer)
]
cb += [
RunningMetricsPlotterCallback(
