Validating correctness and consistency of the Dataset

[hmehryar]

• [Test No. 1: Testing if 9 sample entry with eloss=LBT from using shuffled dataset, return exactly one entry in corresponding config_based_dataset]
• • [Test No. 2: Testing if 3 sample entry with eloss=MATTER from using shuffled dataset, return exactly one entry in corresponding config_based_dataset]

Test No. 1 and 2 procedure:

• Loading Dataset
• Implement a method to get an event and features from Dataset
• Implement a method to find dataset a file by feature name parameters
• Implement loading dataset file with specific config
• Implement a method to find an event inside the config dataset file

[hmehryar]

• [finding 9 samples from the dataset]
• [check if each entry just has one corresponding entry in the 9 config files]

[hmehryar]

TEST#1 results alpha_s: 0.2 q0: 1.5 config_01_alpha_0.2_q0_1.5_MMAT_MLBT_size_1200000_shuffled.pkl file found 1080000(array([['MLBT', '0.2', '1.5'], ['MMAT', '0.2', '1']], dtype='<U32'), array([540000, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True alpha_s: 0.3 q0: 1.5 config_02_alpha_0.3_q0_1.5_MMAT_MLBT_size_1200000_shuffled.pkl file found 1080000(array([['MLBT', '0.3', '1.5'], ['MMAT', '0.3', '1']], dtype='<U32'), array([540000, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True alpha_s: 0.4 q0: 1.5 config_03_alpha_0.4_q0_1.5_MMAT_MLBT_size_1200000_shuffled.pkl file found 1080000(array([['MLBT', '0.4', '1.5'], ['MMAT', '0.4', '1']], dtype='<U32'), array([540000, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True alpha_s: 0.2 q0: 2.0 config_04_alpha_0.2_q0_2.0_MMAT_MLBT_size_1200000_shuffled.pkl file found 1080000(array([['MLBT', '0.2', '2.0'], ['MMAT', '0.2', '1']], dtype='<U32'), array([540000, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True alpha_s: 0.3 q0: 2.0 config_05_alpha_0.3_q0_2.0_MMAT_MLBT_size_1200000_shuffled.pkl file found 1079991(array([['MLBT', '0.3', '2.0'], ['MMAT', '0.3', '1']], dtype='<U32'), array([539991, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True alpha_s: 0.4 q0: 2.0 config_06_alpha_0.4_q0_2.0_MMAT_MLBT_size_1200000_shuffled.pkl file found 1080000(array([['MLBT', '0.4', '2.0'], ['MMAT', '0.4', '1']], dtype='<U32'), array([540000, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True alpha_s: 0.2 q0: 2.5 config_07_alpha_0.2_q0_2.5_MMAT_MLBT_size_1200000_shuffled.pkl file found 1080000(array([['MLBT', '0.2', '2.5'], ['MMAT', '0.2', '1']], dtype='<U32'), array([540000, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True alpha_s: 0.3 q0: 2.5 config_08_alpha_0.3_q0_2.5_MMAT_MLBT_size_1200000_shuffled.pkl file found 1080000(array([['MLBT', '0.3', '2.5'], ['MMAT', '0.3', '1']], dtype='<U32'), array([540000, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True alpha_s: 0.4 q0: 2.5 config_09_alpha_0.4_q0_2.5_MMAT_MLBT_size_1200000_shuffled.pkl file found 1080000(array([['MLBT', '0.4', '2.5'], ['MMAT', '0.4', '1']], dtype='<U32'), array([540000, 540000])) (array([[0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.], [0., 0., 0., ..., 0., 0., 0.]]), array(['MLBT', '0.2', '1.5'], dtype='<U32')) True [True, True, True, True, True, True, True, True, True]

[hmehryar]

loading 10.8m events dataset and refactoring code to work with it accordingly