def test_load_sim_split():
df_train_0, df_test_0 = load_sim(config='IC86.2012',
energy_reco=False,
log_energy_min=None,
log_energy_max=None,
test_size=0.5)
df_train_1, df_test_1 = load_sim(config='IC86.2012',
energy_reco=False,
log_energy_min=None,
log_energy_max=None,
test_size=0.5)
pd.testing.assert_frame_equal(df_train_0, df_train_1)
pd.testing.assert_frame_equal(df_test_0, df_test_1)
def test_load_sim_energy_reco(energy_reco):
df = load_sim(test_size=0,
energy_reco=energy_reco,
log_energy_min=None,
log_energy_max=None)
assert ('reco_log_energy' in df.columns) == energy_reco
def test_load_sim_log_energy_max():
log_energy_max = 7.5
df = load_sim(test_size=0,
energy_reco=False,
energy_cut_key='MC_log_energy',
log_energy_min=None,
log_energy_max=log_energy_max)
np.testing.assert_allclose(log_energy_max,
df['MC_log_energy'].max(),
rtol=1e-2)
def test_load_sim_test_size():
test_size = 0.4
df_train, df_test = load_sim(test_size=test_size,
energy_reco=False,
log_energy_min=None,
log_energy_max=None)
n_train = len(df_train)
n_test = len(df_test)
np.testing.assert_allclose(n_test / (n_test + n_train),
test_size,
rtol=1e-2)