diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index f2d4143..62eebfa 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -26,7 +26,9 @@ repos: rev: v2.2.6 hooks: - id: codespell - args: [-L, livetime] + args: [--toml, pyproject.toml] + additional_dependencies: + - tomli - repo: https://github.com/pre-commit/pygrep-hooks rev: v1.10.0 hooks: diff --git a/configs/biased_selection/biased_muongun.yaml b/configs/biased_selection/biased_muongun.yaml index 3655a00..16d1637 100644 --- a/configs/biased_selection/biased_muongun.yaml +++ b/configs/biased_selection/biased_muongun.yaml @@ -162,7 +162,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/cascade_monopod_cascade_dir_big_kernel.yaml b/configs/event_selection/cascade_monopod_cascade_dir_big_kernel.yaml index 1977115..ea5eb57 100644 --- a/configs/event_selection/cascade_monopod_cascade_dir_big_kernel.yaml +++ b/configs/event_selection/cascade_monopod_cascade_dir_big_kernel.yaml @@ -278,7 +278,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/cascade_monopod_starting_cascades_big_kernel.yaml b/configs/event_selection/cascade_monopod_starting_cascades_big_kernel.yaml index 2fe4385..9fab5f5 100644 --- a/configs/event_selection/cascade_monopod_starting_cascades_big_kernel.yaml +++ b/configs/event_selection/cascade_monopod_starting_cascades_big_kernel.yaml @@ -278,7 +278,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/cascade_monopod_starting_events.yaml b/configs/event_selection/cascade_monopod_starting_events.yaml index 88a9f52..32fdd78 100644 --- a/configs/event_selection/cascade_monopod_starting_events.yaml +++ b/configs/event_selection/cascade_monopod_starting_events.yaml @@ -278,7 +278,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/cascade_monopod_starting_events_big_kernel.yaml b/configs/event_selection/cascade_monopod_starting_events_big_kernel.yaml index 0d41e63..87667a9 100644 --- a/configs/event_selection/cascade_monopod_starting_events_big_kernel.yaml +++ b/configs/event_selection/cascade_monopod_starting_events_big_kernel.yaml @@ -278,7 +278,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/cascade_monopod_starting_pid_big_kernel.yaml b/configs/event_selection/cascade_monopod_starting_pid_big_kernel.yaml index 54d9e96..0e508bc 100644 --- a/configs/event_selection/cascade_monopod_starting_pid_big_kernel.yaml +++ b/configs/event_selection/cascade_monopod_starting_pid_big_kernel.yaml @@ -278,7 +278,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3a_starting_events.yaml b/configs/event_selection/dnn_cscd_l3a_starting_events.yaml index ad692b9..ae106ce 100644 --- a/configs/event_selection/dnn_cscd_l3a_starting_events.yaml +++ b/configs/event_selection/dnn_cscd_l3a_starting_events.yaml @@ -306,7 +306,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b/dnn_cscd_l3b_cut2_starting_events_300m_fast_medium.yaml b/configs/event_selection/dnn_cscd_l3b/dnn_cscd_l3b_cut2_starting_events_300m_fast_medium.yaml index 3faa6f4..fe8d83e 100644 --- a/configs/event_selection/dnn_cscd_l3b/dnn_cscd_l3b_cut2_starting_events_300m_fast_medium.yaml +++ b/configs/event_selection/dnn_cscd_l3b/dnn_cscd_l3b_cut2_starting_events_300m_fast_medium.yaml @@ -202,7 +202,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b/dnn_cscd_l3b_cut2_starting_events_300m_fast_small.yaml b/configs/event_selection/dnn_cscd_l3b/dnn_cscd_l3b_cut2_starting_events_300m_fast_small.yaml index 284f8e6..ea98219 100644 --- a/configs/event_selection/dnn_cscd_l3b/dnn_cscd_l3b_cut2_starting_events_300m_fast_small.yaml +++ b/configs/event_selection/dnn_cscd_l3b/dnn_cscd_l3b_cut2_starting_events_300m_fast_small.yaml @@ -202,7 +202,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b_starting_cascades_big_kernel.yaml b/configs/event_selection/dnn_cscd_l3b_starting_cascades_big_kernel.yaml index 7629de7..2f8097f 100644 --- a/configs/event_selection/dnn_cscd_l3b_starting_cascades_big_kernel.yaml +++ b/configs/event_selection/dnn_cscd_l3b_starting_cascades_big_kernel.yaml @@ -91,7 +91,7 @@ # Additional MuonGun at CscdL3 '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/12*/0.99_eff/00*000-00*999/*.hdf5', - # Manuel Silva's MuonGun + # Manuel's MuonGun '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/2131*/00*000-00*999/*.hdf5', # Additional MuonGun biased simulation: corner clippers @@ -177,7 +177,7 @@ # # Additional MuonGun at CscdL3 # '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/12*/0.99_eff/00*000-00*999/*.hdf5', - # # Manuel Silva's MuonGun + # # Manuel's MuonGun # '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/2131*/00*000-00*999/*.hdf5', # # Additional MuonGun biased simulation: corner clippers @@ -323,7 +323,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b_starting_cascades_big_kernel_strict.yaml b/configs/event_selection/dnn_cscd_l3b_starting_cascades_big_kernel_strict.yaml index 1180b25..6c1aae1 100644 --- a/configs/event_selection/dnn_cscd_l3b_starting_cascades_big_kernel_strict.yaml +++ b/configs/event_selection/dnn_cscd_l3b_starting_cascades_big_kernel_strict.yaml @@ -91,7 +91,7 @@ # Additional MuonGun at CscdL3 '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/12*/0.99_eff/00*000-00*999/*.hdf5', - # Manuel Silva's MuonGun + # Manuel's MuonGun '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/2131*/00*000-00*999/*.hdf5', # Additional MuonGun biased simulation: corner clippers @@ -177,7 +177,7 @@ # # Additional MuonGun at CscdL3 # '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/12*/0.99_eff/00*000-00*999/*.hdf5', - # # Manuel Silva's MuonGun + # # Manuel's MuonGun # '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/2131*/00*000-00*999/*.hdf5', # # Additional MuonGun biased simulation: corner clippers @@ -323,7 +323,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b_starting_events.yaml b/configs/event_selection/dnn_cscd_l3b_starting_events.yaml index e7b3604..4ea1fe1 100644 --- a/configs/event_selection/dnn_cscd_l3b_starting_events.yaml +++ b/configs/event_selection/dnn_cscd_l3b_starting_events.yaml @@ -306,7 +306,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b_starting_events_big_kernel.yaml b/configs/event_selection/dnn_cscd_l3b_starting_events_big_kernel.yaml index 797194a..3d854f2 100644 --- a/configs/event_selection/dnn_cscd_l3b_starting_events_big_kernel.yaml +++ b/configs/event_selection/dnn_cscd_l3b_starting_events_big_kernel.yaml @@ -91,7 +91,7 @@ # Additional MuonGun at CscdL3 '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/12*/0.99_eff/00*000-00*999/*.hdf5', - # Manuel Silva's MuonGun + # Manuel's MuonGun '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/2131*/00*000-00*999/*.hdf5', # Additional MuonGun biased simulation: corner clippers @@ -177,7 +177,7 @@ # # Additional MuonGun at CscdL3 # '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/12*/0.99_eff/00*000-00*999/*.hdf5', - # # Manuel Silva's MuonGun + # # Manuel's MuonGun # '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/dnn_cscd_l3b/MuonGun/2131*/00*000-00*999/*.hdf5', # # Additional MuonGun biased simulation: corner clippers @@ -323,7 +323,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b_starting_events_default_model.yaml b/configs/event_selection/dnn_cscd_l3b_starting_events_default_model.yaml index bfcd15a..b1fbedf 100644 --- a/configs/event_selection/dnn_cscd_l3b_starting_events_default_model.yaml +++ b/configs/event_selection/dnn_cscd_l3b_starting_events_default_model.yaml @@ -306,7 +306,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b_starting_events_default_model_unweighted.yaml b/configs/event_selection/dnn_cscd_l3b_starting_events_default_model_unweighted.yaml index 129a42b..ac55784 100644 --- a/configs/event_selection/dnn_cscd_l3b_starting_events_default_model_unweighted.yaml +++ b/configs/event_selection/dnn_cscd_l3b_starting_events_default_model_unweighted.yaml @@ -306,7 +306,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3b_starting_events_unweighted.yaml b/configs/event_selection/dnn_cscd_l3b_starting_events_unweighted.yaml index 2738b62..c0cdb77 100644 --- a/configs/event_selection/dnn_cscd_l3b_starting_events_unweighted.yaml +++ b/configs/event_selection/dnn_cscd_l3b_starting_events_unweighted.yaml @@ -306,7 +306,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_cut2_starting_events_300m_fast_medium.yaml b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_cut2_starting_events_300m_fast_medium.yaml index 1b6c3bd..dc43687 100644 --- a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_cut2_starting_events_300m_fast_medium.yaml +++ b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_cut2_starting_events_300m_fast_medium.yaml @@ -246,7 +246,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_pid_nutau_cc_vs_nue_cc.yaml b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_pid_nutau_cc_vs_nue_cc.yaml index 039fc06..9d4a2ea 100644 --- a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_pid_nutau_cc_vs_nue_cc.yaml +++ b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_pid_nutau_cc_vs_nue_cc.yaml @@ -227,7 +227,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_in_detector_length.yaml b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_in_detector_length.yaml index afa6cb3..29239fd 100644 --- a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_in_detector_length.yaml +++ b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_in_detector_length.yaml @@ -209,7 +209,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_numu_cc_vs_nue_cc.yaml b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_numu_cc_vs_nue_cc.yaml index 8b9c7ae..dd14b63 100644 --- a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_numu_cc_vs_nue_cc.yaml +++ b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_numu_cc_vs_nue_cc.yaml @@ -225,7 +225,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_numu_cc_vs_starting.yaml b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_numu_cc_vs_starting.yaml index 7655aae..e149d7b 100644 --- a/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_numu_cc_vs_starting.yaml +++ b/configs/event_selection/dnn_cscd_l3c/dnn_cscd_l3c_track_numu_cc_vs_starting.yaml @@ -208,7 +208,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_seed/event_selection_egen_seed.yaml b/configs/event_selection/egen_seed/event_selection_egen_seed.yaml index 9dff1c1..e7ab352 100644 --- a/configs/event_selection/egen_seed/event_selection_egen_seed.yaml +++ b/configs/event_selection/egen_seed/event_selection_egen_seed.yaml @@ -18,7 +18,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -30,7 +30,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -39,13 +39,13 @@ ] 'validation_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] 'test_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] @@ -166,7 +166,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_seed/event_selection_egen_seed_dir.yaml b/configs/event_selection/egen_seed/event_selection_egen_seed_dir.yaml index 1e9e46d..a5b124a 100644 --- a/configs/event_selection/egen_seed/event_selection_egen_seed_dir.yaml +++ b/configs/event_selection/egen_seed/event_selection_egen_seed_dir.yaml @@ -18,7 +18,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -30,7 +30,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -39,13 +39,13 @@ ] 'validation_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] 'test_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] @@ -166,7 +166,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_seed/event_selection_egen_seed_energy.yaml b/configs/event_selection/egen_seed/event_selection_egen_seed_energy.yaml index 37ec87c..2c45445 100644 --- a/configs/event_selection/egen_seed/event_selection_egen_seed_energy.yaml +++ b/configs/event_selection/egen_seed/event_selection_egen_seed_energy.yaml @@ -18,7 +18,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -30,7 +30,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -39,13 +39,13 @@ ] 'validation_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] 'test_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] @@ -166,7 +166,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_seed/event_selection_egen_seed_pos.yaml b/configs/event_selection/egen_seed/event_selection_egen_seed_pos.yaml index 55de13e..29c44cc 100644 --- a/configs/event_selection/egen_seed/event_selection_egen_seed_pos.yaml +++ b/configs/event_selection/egen_seed/event_selection_egen_seed_pos.yaml @@ -18,7 +18,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -30,7 +30,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -39,13 +39,13 @@ ] 'validation_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] 'test_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] @@ -166,7 +166,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_seed/event_selection_egen_seed_time.yaml b/configs/event_selection/egen_seed/event_selection_egen_seed_time.yaml index 0e4edc5..7e76f7d 100644 --- a/configs/event_selection/egen_seed/event_selection_egen_seed_time.yaml +++ b/configs/event_selection/egen_seed/event_selection_egen_seed_time.yaml @@ -18,7 +18,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -30,7 +30,7 @@ '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/00000-00999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/new/Nu*/*_energy/*/l2/01000-01999/*.hdf5', - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0000000-0000999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0001000-0001999/*.hdf5', '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0002000-0002999/*.hdf5', @@ -39,13 +39,13 @@ ] 'validation_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] 'test_data_file' : [ - # Manuels NuGen Spice3.2.1 (with coincident events) + # Manuel's NuGen Spice3.2.1 (with coincident events) '/net/big-tank/POOL/users/mhuennefeld/data/event_selection/training_data/egen_seed/NuGen/2121*/0004000-0004999/*.hdf5', ] @@ -166,7 +166,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_vertex/egen_vertex_pid.yaml b/configs/event_selection/egen_vertex/egen_vertex_pid.yaml index 872d3cc..8876331 100644 --- a/configs/event_selection/egen_vertex/egen_vertex_pid.yaml +++ b/configs/event_selection/egen_vertex/egen_vertex_pid.yaml @@ -209,7 +209,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_vertex/egen_vertex_pid_nue_cc_vs_nue_nc.yaml b/configs/event_selection/egen_vertex/egen_vertex_pid_nue_cc_vs_nue_nc.yaml index 9864b4b..6c4c84b 100644 --- a/configs/event_selection/egen_vertex/egen_vertex_pid_nue_cc_vs_nue_nc.yaml +++ b/configs/event_selection/egen_vertex/egen_vertex_pid_nue_cc_vs_nue_nc.yaml @@ -214,7 +214,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_vertex/egen_vertex_pid_nue_cc_vs_nutau_cc.yaml b/configs/event_selection/egen_vertex/egen_vertex_pid_nue_cc_vs_nutau_cc.yaml index 1fa5f32..3a17c88 100644 --- a/configs/event_selection/egen_vertex/egen_vertex_pid_nue_cc_vs_nutau_cc.yaml +++ b/configs/event_selection/egen_vertex/egen_vertex_pid_nue_cc_vs_nutau_cc.yaml @@ -220,7 +220,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_vertex/egen_vertex_starting_events_300m_fast_medium.yaml b/configs/event_selection/egen_vertex/egen_vertex_starting_events_300m_fast_medium.yaml index 0b42033..6bf6198 100644 --- a/configs/event_selection/egen_vertex/egen_vertex_starting_events_300m_fast_medium.yaml +++ b/configs/event_selection/egen_vertex/egen_vertex_starting_events_300m_fast_medium.yaml @@ -246,7 +246,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_vertex/egen_vertex_starting_nue_300m_fast_medium.yaml b/configs/event_selection/egen_vertex/egen_vertex_starting_nue_300m_fast_medium.yaml index d8abcd7..6a58069 100644 --- a/configs/event_selection/egen_vertex/egen_vertex_starting_nue_300m_fast_medium.yaml +++ b/configs/event_selection/egen_vertex/egen_vertex_starting_nue_300m_fast_medium.yaml @@ -251,7 +251,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_vertex/egen_vertex_track_in_detector_length.yaml b/configs/event_selection/egen_vertex/egen_vertex_track_in_detector_length.yaml index 0bad073..55cdaa7 100644 --- a/configs/event_selection/egen_vertex/egen_vertex_track_in_detector_length.yaml +++ b/configs/event_selection/egen_vertex/egen_vertex_track_in_detector_length.yaml @@ -209,7 +209,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_vertex/egen_vertex_track_numu_cc_vs_nue_cc.yaml b/configs/event_selection/egen_vertex/egen_vertex_track_numu_cc_vs_nue_cc.yaml index 137b4d6..14d48d4 100644 --- a/configs/event_selection/egen_vertex/egen_vertex_track_numu_cc_vs_nue_cc.yaml +++ b/configs/event_selection/egen_vertex/egen_vertex_track_numu_cc_vs_nue_cc.yaml @@ -225,7 +225,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/egen_vertex/egen_vertex_track_numu_cc_vs_starting.yaml b/configs/event_selection/egen_vertex/egen_vertex_track_numu_cc_vs_starting.yaml index 426ae95..960465c 100644 --- a/configs/event_selection/egen_vertex/egen_vertex_track_numu_cc_vs_starting.yaml +++ b/configs/event_selection/egen_vertex/egen_vertex_track_numu_cc_vs_starting.yaml @@ -208,7 +208,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_astroness.yaml b/configs/event_selection/event_selection_astroness.yaml index 85447a9..8334cc1 100644 --- a/configs/event_selection/event_selection_astroness.yaml +++ b/configs/event_selection/event_selection_astroness.yaml @@ -307,7 +307,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_cascade_dir.yaml b/configs/event_selection/event_selection_cascade_dir.yaml index 5391a8d..73eb7da 100644 --- a/configs/event_selection/event_selection_cascade_dir.yaml +++ b/configs/event_selection/event_selection_cascade_dir.yaml @@ -310,7 +310,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_cascade_energy.yaml b/configs/event_selection/event_selection_cascade_energy.yaml index c910497..ff63fb7 100644 --- a/configs/event_selection/event_selection_cascade_energy.yaml +++ b/configs/event_selection/event_selection_cascade_energy.yaml @@ -309,7 +309,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_cascade_pos.yaml b/configs/event_selection/event_selection_cascade_pos.yaml index e4c4c0b..7f76a26 100644 --- a/configs/event_selection/event_selection_cascade_pos.yaml +++ b/configs/event_selection/event_selection_cascade_pos.yaml @@ -308,7 +308,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_cascade_t.yaml b/configs/event_selection/event_selection_cascade_t.yaml index 5084bf4..d374cf5 100644 --- a/configs/event_selection/event_selection_cascade_t.yaml +++ b/configs/event_selection/event_selection_cascade_t.yaml @@ -308,7 +308,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_entering.yaml b/configs/event_selection/event_selection_entering.yaml index e2f542e..78df72e 100644 --- a/configs/event_selection/event_selection_entering.yaml +++ b/configs/event_selection/event_selection_entering.yaml @@ -307,7 +307,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_nugen_l2_reconstruction.yaml b/configs/event_selection/event_selection_nugen_l2_reconstruction.yaml index 3cdc4f1..0c8c6b2 100644 --- a/configs/event_selection/event_selection_nugen_l2_reconstruction.yaml +++ b/configs/event_selection/event_selection_nugen_l2_reconstruction.yaml @@ -133,7 +133,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_nugen_l2_reconstruction_big.yaml b/configs/event_selection/event_selection_nugen_l2_reconstruction_big.yaml index 36b1201..24c59f5 100644 --- a/configs/event_selection/event_selection_nugen_l2_reconstruction_big.yaml +++ b/configs/event_selection/event_selection_nugen_l2_reconstruction_big.yaml @@ -307,7 +307,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_pid.yaml b/configs/event_selection/event_selection_pid.yaml index dd15821..e81b854 100644 --- a/configs/event_selection/event_selection_pid.yaml +++ b/configs/event_selection/event_selection_pid.yaml @@ -312,7 +312,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_starting_cascades.yaml b/configs/event_selection/event_selection_starting_cascades.yaml index 4266c42..68f7073 100644 --- a/configs/event_selection/event_selection_starting_cascades.yaml +++ b/configs/event_selection/event_selection_starting_cascades.yaml @@ -307,7 +307,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_starting_events.yaml b/configs/event_selection/event_selection_starting_events.yaml index ee0502d..38fdccc 100644 --- a/configs/event_selection/event_selection_starting_events.yaml +++ b/configs/event_selection/event_selection_starting_events.yaml @@ -306,7 +306,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_starting_events_big.yaml b/configs/event_selection/event_selection_starting_events_big.yaml index 2d15402..667e73a 100644 --- a/configs/event_selection/event_selection_starting_events_big.yaml +++ b/configs/event_selection/event_selection_starting_events_big.yaml @@ -271,7 +271,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_track_detectorlength.yaml b/configs/event_selection/event_selection_track_detectorlength.yaml index ac8ab4c..1cb722c 100644 --- a/configs/event_selection/event_selection_track_detectorlength.yaml +++ b/configs/event_selection/event_selection_track_detectorlength.yaml @@ -308,7 +308,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_track_dir.yaml b/configs/event_selection/event_selection_track_dir.yaml index a30723b..4fa15a7 100644 --- a/configs/event_selection/event_selection_track_dir.yaml +++ b/configs/event_selection/event_selection_track_dir.yaml @@ -309,7 +309,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_track_energy.yaml b/configs/event_selection/event_selection_track_energy.yaml index b3da131..068c1ea 100644 --- a/configs/event_selection/event_selection_track_energy.yaml +++ b/configs/event_selection/event_selection_track_energy.yaml @@ -308,7 +308,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_track_length.yaml b/configs/event_selection/event_selection_track_length.yaml index 1012141..c6dd2f2 100644 --- a/configs/event_selection/event_selection_track_length.yaml +++ b/configs/event_selection/event_selection_track_length.yaml @@ -305,7 +305,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_track_pos.yaml b/configs/event_selection/event_selection_track_pos.yaml index c89343f..c88b89d 100644 --- a/configs/event_selection/event_selection_track_pos.yaml +++ b/configs/event_selection/event_selection_track_pos.yaml @@ -307,7 +307,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/event_selection_upgoing_tracks.yaml b/configs/event_selection/event_selection_upgoing_tracks.yaml index 581f35e..3ec3df6 100644 --- a/configs/event_selection/event_selection_upgoing_tracks.yaml +++ b/configs/event_selection/event_selection_upgoing_tracks.yaml @@ -317,7 +317,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. @@ -345,7 +345,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_cascades_150m_red_summary_stats_fast.yaml b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_cascades_150m_red_summary_stats_fast.yaml index be9e98f..04709f0 100644 --- a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_cascades_150m_red_summary_stats_fast.yaml +++ b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_cascades_150m_red_summary_stats_fast.yaml @@ -194,7 +194,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_150m_red_summary_stats_fast.yaml b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_150m_red_summary_stats_fast.yaml index 82ef732..c2785ff 100644 --- a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_150m_red_summary_stats_fast.yaml +++ b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_150m_red_summary_stats_fast.yaml @@ -193,7 +193,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_300m_red_summary_stats_fast.yaml b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_300m_red_summary_stats_fast.yaml index 60c14c1..fc54677 100644 --- a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_300m_red_summary_stats_fast.yaml +++ b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_300m_red_summary_stats_fast.yaml @@ -193,7 +193,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_red_summary_stats_fast.yaml b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_red_summary_stats_fast.yaml index 1b44b62..1b45860 100644 --- a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_red_summary_stats_fast.yaml +++ b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_red_summary_stats_fast.yaml @@ -173,7 +173,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_total_dom_charge_fast.yaml b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_total_dom_charge_fast.yaml index e9b7e70..f1e0e27 100644 --- a/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_total_dom_charge_fast.yaml +++ b/configs/event_selection/pre_selection/dnn_cscd_l3a_starting_events_total_dom_charge_fast.yaml @@ -173,7 +173,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/veto_classifier/event_selection_veto_classifier__downgoing.yaml b/configs/event_selection/veto_classifier/event_selection_veto_classifier__downgoing.yaml index 5b02468..c2cb676 100644 --- a/configs/event_selection/veto_classifier/event_selection_veto_classifier__downgoing.yaml +++ b/configs/event_selection/veto_classifier/event_selection_veto_classifier__downgoing.yaml @@ -185,7 +185,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early.yaml b/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early.yaml index 529d33e..37382d1 100644 --- a/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early.yaml +++ b/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early.yaml @@ -239,7 +239,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early__downgoing.yaml b/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early__downgoing.yaml index 9331495..d19427e 100644 --- a/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early__downgoing.yaml +++ b/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early__downgoing.yaml @@ -185,7 +185,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early_with_energy.yaml b/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early_with_energy.yaml index d17cb62..ab8849d 100644 --- a/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early_with_energy.yaml +++ b/configs/event_selection/veto_classifier/event_selection_veto_classifier_vertex_early_with_energy.yaml @@ -239,7 +239,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/muon_scattering/muon_scattering.yaml b/configs/muon_scattering/muon_scattering.yaml index 192ec6a..b61e6d7 100644 --- a/configs/muon_scattering/muon_scattering.yaml +++ b/configs/muon_scattering/muon_scattering.yaml @@ -191,7 +191,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/muon_scattering/muon_scattering_L200_Lb100_La100_E10_r0_40.yaml b/configs/muon_scattering/muon_scattering_L200_Lb100_La100_E10_r0_40.yaml index 9e67dc6..28df28a 100644 --- a/configs/muon_scattering/muon_scattering_L200_Lb100_La100_E10_r0_40.yaml +++ b/configs/muon_scattering/muon_scattering_L200_Lb100_La100_E10_r0_40.yaml @@ -209,7 +209,7 @@ data_handler_nan_fill_value: 0. #----------------------- Use this with CAUTION! # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/muon_scattering/muon_scattering_energy.yaml b/configs/muon_scattering/muon_scattering_energy.yaml index 16663af..7fc3d2d 100644 --- a/configs/muon_scattering/muon_scattering_energy.yaml +++ b/configs/muon_scattering/muon_scattering_energy.yaml @@ -209,7 +209,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/muon_scattering/muon_scattering_tracks.yaml b/configs/muon_scattering/muon_scattering_tracks.yaml index d6e9deb..b5a4ed4 100644 --- a/configs/muon_scattering/muon_scattering_tracks.yaml +++ b/configs/muon_scattering/muon_scattering_tracks.yaml @@ -191,7 +191,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/stopping_muons/stopping_muons_hoinka_no_filter.yaml b/configs/stopping_muons/stopping_muons_hoinka_no_filter.yaml index 411b153..798582c 100644 --- a/configs/stopping_muons/stopping_muons_hoinka_no_filter.yaml +++ b/configs/stopping_muons/stopping_muons_hoinka_no_filter.yaml @@ -158,7 +158,7 @@ data_handler_nan_fill_value : 0. # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/stopping_muons/stopping_muons_hoinka_no_filter__direction.yaml b/configs/stopping_muons/stopping_muons_hoinka_no_filter__direction.yaml index 40f57dd..0915657 100644 --- a/configs/stopping_muons/stopping_muons_hoinka_no_filter__direction.yaml +++ b/configs/stopping_muons/stopping_muons_hoinka_no_filter__direction.yaml @@ -159,7 +159,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/stopping_muons/stopping_muons_hoinka_no_filter__energy.yaml b/configs/stopping_muons/stopping_muons_hoinka_no_filter__energy.yaml index 354b95b..86c91fe 100644 --- a/configs/stopping_muons/stopping_muons_hoinka_no_filter__energy.yaml +++ b/configs/stopping_muons/stopping_muons_hoinka_no_filter__energy.yaml @@ -159,7 +159,7 @@ # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/configs/stopping_muons/stopping_muons_hoinka_no_filter__stopping_rz.yaml b/configs/stopping_muons/stopping_muons_hoinka_no_filter__stopping_rz.yaml index 839bd76..e1f4b2a 100644 --- a/configs/stopping_muons/stopping_muons_hoinka_no_filter__stopping_rz.yaml +++ b/configs/stopping_muons/stopping_muons_hoinka_no_filter__stopping_rz.yaml @@ -161,7 +161,7 @@ data_handler_nan_fill_value : 0. # ---------------- # Biased Selection # ---------------- -# Filter events based on the curent reconstruction performance on these +# Filter events based on the current reconstruction performance on these # by defining key, value pairs and a biased fraction. # Events will be put in queues, such that biased_fraction of all events # passes one of the defined cuts. diff --git a/dnn_reco/data_handler.py b/dnn_reco/data_handler.py index b96264c..633ff0a 100644 --- a/dnn_reco/data_handler.py +++ b/dnn_reco/data_handler.py @@ -37,7 +37,7 @@ class DataHandler(object): misc_data_exists : bool If true, misc data exists and is != None. misc_names : list of str - Names of misc names. If no misc data exists, this is an emtpy list. + Names of misc names. If no misc data exists, this is an empty list. misc_shape : list of int Shape of misc data without batch dimension. num_bins : int @@ -243,7 +243,7 @@ def read_icecube_data( Entries with nan values will be replaced by this value. If None, no replacement will be performed. init_values : float, optional - The x_ic78 array will be initalized with these values via: + The x_ic78 array will be initialized with these values via: np.zeros_like(x_ic78) * np.array(init_values) verbose : bool, optional Print out additional information on runtimes for loading and @@ -521,7 +521,7 @@ def get_batch_generator( 2) Another worker aggregates the events of several files (number of files defined by 'num_add_files') together - by dequeing elements from the 'data_batch_queue'. + by dequeuing elements from the 'data_batch_queue'. It then creates batches from these events (randomly if sample_randomly == True ). These batches are then put onto the 'final_batch_queue'. @@ -559,16 +559,16 @@ def get_batch_generator( of size 'batch_size'. This queue is what is used to obtain the final batches, which the generator yields. num_jobs : int, optional - Number of jobs to run in parrallel to load and process input files. + Number of jobs to run in parallel to load and process input files. num_add_files : int, optional - Defines how many files are additionaly loaded at once. + Defines how many files are additionally loaded at once. Batches will be generated among events of these (1 + num_add_files) files num_repetitions : int, optional Number of times the events in a loaded file are to be used, before new files are loaded. init_values : float, optional - The x_ic78 array will be initalized with these values via: + The x_ic78 array will be initialized with these values via: np.zeros_like(x_ic78) * np.array(init_values) num_splits : int, optional If num_splits is given, the loaded file will be divided into @@ -1067,7 +1067,7 @@ def _create_model(self, cfg, cfg_sel): sess=sess, ) - # compile model: initalize and finalize graph + # compile model: initialize and finalize graph model.compile() # restore model weights diff --git a/dnn_reco/data_trafo.py b/dnn_reco/data_trafo.py index 896bece..2ac67ae 100644 --- a/dnn_reco/data_trafo.py +++ b/dnn_reco/data_trafo.py @@ -68,7 +68,7 @@ def __init__( The natural logarithm is applied to the misc data bins prior to normalization. If a list is given, the length of the list must match the number of - misc variabels misc_shape[-1]. The logarithm is applied to bin i + misc variables misc_shape[-1]. The logarithm is applied to bin i if the ith entry of the log_misc_bins list is True. If a dictionary is provided, a list of length label_shape[-1] will be initialized with False and only the values of the labels as @@ -200,7 +200,7 @@ def _perform_update_step(self, log_bins, data_batch, n, mean, M2): Parameters ---------- log_bins : list of bool - Defines whether the natural logarithm is appllied to bins along + Defines whether the natural logarithm is applied to bins along last axis. Must have same length as data_batch.shape[-1]. data_batch : numpy ndarray A batch of data for which to update the variance variables of the @@ -308,7 +308,7 @@ def create_trafo_model_iteratively(self, data_iterator, num_batches): # combine DOM data over all DOMs if desired if self.trafo_model["treat_doms_equally"]: - # initalize with zeros + # initialize with zeros self.trafo_model["ic78_mean"] = np.zeros(self._ic78_shape) self.trafo_model["ic78_std"] = np.zeros(self._ic78_shape) @@ -425,7 +425,7 @@ def _check_settings(self, data, data_type): ------ ValueError If DataTransformer object has not created or loaded a trafo model. - If provided data_type is unkown. + If provided data_type is unknown. """ dtype = data.dtype data_type = data_type.lower() @@ -506,7 +506,7 @@ def transform(self, data, data_type, bias_correction=True): ---------------- ValueError If DataTransformer object has not created or loaded a trafo model. - If provided data_type is unkown. + If provided data_type is unknown. """ data, log_name, normalize_name, log_func, exp_func, is_tf, dtype = ( self._check_settings(data, data_type) @@ -570,14 +570,14 @@ def inverse_transform(self, data, data_type, bias_correction=True): Returns ------- type(data) - Returns the inverse transformed DOM respones and + Returns the inverse transformed DOM responses and cascade_parameters. No Longer Raises ---------------- ValueError If DataTransformer object has not created or loaded a trafo model. - If provided data_type is unkown. + If provided data_type is unknown. """ data, log_name, normalize_name, log_func, exp_func, is_tf, dtype = ( self._check_settings(data, data_type) diff --git a/dnn_reco/ic3/llh.py b/dnn_reco/ic3/llh.py index c890e9d..49de083 100644 --- a/dnn_reco/ic3/llh.py +++ b/dnn_reco/ic3/llh.py @@ -700,7 +700,7 @@ def cdf_dir(self, dir_x, dir_y, dir_z): Returns ------- np.array - The cumulative probabilty for the given direction vectors. + The cumulative probability for the given direction vectors. """ if not self.is_normalized(dir_x, dir_y, dir_z): print("cdf_dir is normalizing direction vectors") @@ -714,7 +714,7 @@ def cdf_dir(self, dir_x, dir_y, dir_z): return cdf def _get_level_indices(self, level=0.5, delta=0.01): - """Get indices of sampled diections, which belong to the specified + """Get indices of sampled directions, which belong to the specified contour as defined by: level +- delta. Parameters @@ -1047,7 +1047,7 @@ def cdf_dir(self, dir_x, dir_y, dir_z): Returns ------- np.array - The cumulative probabilty for the given direction vectors. + The cumulative probability for the given direction vectors. """ if not self.is_normalized(dir_x, dir_y, dir_z): print("cdf_dir is normalizing direction vectors") @@ -1059,7 +1059,7 @@ def cdf_dir(self, dir_x, dir_y, dir_z): return cdf def _get_level_indices(self, level=0.5, delta=0.001): - """Get indices of sampled diections, which belong to the specified + """Get indices of sampled directions, which belong to the specified contour as defined by: level +- delta. Parameters diff --git a/dnn_reco/ic3/llh_base.py b/dnn_reco/ic3/llh_base.py index d50b875..fa8b049 100644 --- a/dnn_reco/ic3/llh_base.py +++ b/dnn_reco/ic3/llh_base.py @@ -420,7 +420,7 @@ def cdf(self, zenith, azimuth): Returns ------- np.array - The cumulative probabilty for the given zenith/azimuth pairs. + The cumulative probability for the given zenith/azimuth pairs. """ dir_x, dir_y, dir_z = self.get_dir_vec(zenith, azimuth) return self.cdf_dir(dir_x, dir_y, dir_z) @@ -440,12 +440,12 @@ def cdf_dir(self, dir_x, dir_y, dir_z): Returns ------- np.array - The cumulative probabilty for the given direction vectors. + The cumulative probability for the given direction vectors. """ raise NotImplementedError def _get_level_indices(self, level=0.5, delta=0.01): - """Get indices of sampled diections, which belong to the specified + """Get indices of sampled directions, which belong to the specified contour as defined by: level +- delta. Parameters @@ -824,7 +824,7 @@ def cdf(self, zenith, azimuth): Returns ------- np.array - The cumulative probabilty for the given zenith/azimuth pairs. + The cumulative probability for the given zenith/azimuth pairs. """ neg_llh = -self.log_prob(zenith, azimuth) pos = np.searchsorted(self.neg_llh_values, neg_llh) @@ -846,12 +846,12 @@ def cdf_dir(self, dir_x, dir_y, dir_z): Returns ------- np.array - The cumulative probabilty for the given direction vectors. + The cumulative probability for the given direction vectors. """ return self.cdf(*self.get_zenith_azimuth(dir_x, dir_y, dir_z)) def _get_level_indices(self, level=0.5, delta=0.01): - """Get indices of sampled diections, which belong to the specified + """Get indices of sampled directions, which belong to the specified contour as defined by: level +- delta. Parameters diff --git a/dnn_reco/ic3/modules.py b/dnn_reco/ic3/modules.py index 3112c1b..e8fcabe 100644 --- a/dnn_reco/ic3/modules.py +++ b/dnn_reco/ic3/modules.py @@ -23,7 +23,7 @@ class DeepLearningReco(icetray.I3ConditionalModule): ---------- batch_size : int, optional The number of events to accumulate and pass through the network in - parallel. A higher batch size than 1 can usually improve recontruction + parallel. A higher batch size than 1 can usually improve reconstruction runtime, but will also increase the memory footprint. config : dict Dictionary with configuration settings @@ -94,11 +94,11 @@ def Configure(self): self._output_key = self.GetParameter("OutputBaseName") self._measure_time = self.GetParameter("MeasureTime") self._parallelism_threads = self.GetParameter("ParallelismThreads") - self._ingore_list = self.GetParameter( + self._ignore_list = self.GetParameter( "IgnoreMisconfiguredSettingsList" ) - if self._ingore_list is None: - self._ingore_list = [] + if self._ignore_list is None: + self._ignore_list = [] # read in and combine config files and set up training_files = glob.glob( @@ -176,10 +176,10 @@ def Configure(self): continue if not self._container.config[k] == data_config[k]: - if k in self._ingore_list: + if k in self._ignore_list: msg = "Warning: parameter {!r} is set to {!r} which " msg += "differs from the model [{!r}] default value {!r}. " - msg += "This mismatch will be ingored since the parameter " + msg += "This mismatch will be ignored since the parameter " msg += "is in the IgnoreMisconfiguredSettingsList. " msg += "Make sure this is what you intend to do!" logging.warning( @@ -273,7 +273,7 @@ def Configure(self): sess=sess, ) - # compile model: initalize and finalize graph + # compile model: initialize and finalize graph self.model.compile() # restore model weights diff --git a/dnn_reco/ic3/segments.py b/dnn_reco/ic3/segments.py index 8d5b0fc..353e757 100644 --- a/dnn_reco/ic3/segments.py +++ b/dnn_reco/ic3/segments.py @@ -74,7 +74,7 @@ def ApplyDNNRecos( If True, the run-time will be measured. batch_size : int, optional The number of events to accumulate and pass through the network in - parallel. A higher batch size than 1 can usually improve recontruction + parallel. A higher batch size than 1 can usually improve reconstruction runtime, but will also increase the memory footprint. num_cpus : int, optional Number of CPU cores to use if CPUs are used instead of a GPU. diff --git a/dnn_reco/model.py b/dnn_reco/model.py index 9a332d8..cf0025d 100644 --- a/dnn_reco/model.py +++ b/dnn_reco/model.py @@ -30,7 +30,7 @@ class NNModel(object): saver : tensorflow.train.Saver A tensorflow saver used to save and load model weights. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. """ @@ -75,7 +75,7 @@ def __init__( # create tensorflow placeholders for input data self._setup_placeholders() - # initalize label weights and non zero mask + # initialize label weights and non zero mask self._intialize_label_weights() # build NN architecture @@ -632,7 +632,7 @@ def _merge_tensorboard_summaries(self): ) def _initialize_and_finalize_model(self): - """Initalize and finalize model weights""" + """Initialize and finalize model weights""" # initialize variables self.sess.run(tf.compat.v1.global_variables_initializer()) @@ -879,7 +879,7 @@ def fit( train_result = self.sess.run(train_ops, feed_dict=feed_dict) # ------------------------------------- - # calculate variabels for tukey scaling + # calculate variables for tukey scaling # ------------------------------------- if self.config["label_scale_tukey"]: batch_median_abs_dev = np.median( @@ -899,7 +899,7 @@ def fit( ) # -------------------------------------------- - # calculate online variabels for label weights + # calculate online variables for label weights # -------------------------------------------- if self.config["label_update_weights"]: mse_values_trafo = train_result["mse_values_trafo"] @@ -1151,7 +1151,7 @@ def count_parameters(self, var_list=None): Parameters ---------- var_list : list of tf.Tensors, optional - A list of tensorflow tensors for which to calculate the nubmer of + A list of tensorflow tensors for which to calculate the number of trainable parameters. If None, then all trainable parameters available will be counted. diff --git a/dnn_reco/modules/data/event_weights/event_weights.py b/dnn_reco/modules/data/event_weights/event_weights.py index b2552e7..182fdb5 100644 --- a/dnn_reco/modules/data/event_weights/event_weights.py +++ b/dnn_reco/modules/data/event_weights/event_weights.py @@ -12,7 +12,7 @@ An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -47,7 +47,7 @@ def event_selection_weight( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -106,7 +106,7 @@ def clipped_astroness_weights( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. diff --git a/dnn_reco/modules/data/event_weights/nersc_gnn_event_weights.py b/dnn_reco/modules/data/event_weights/nersc_gnn_event_weights.py index dedd91c..de819a2 100644 --- a/dnn_reco/modules/data/event_weights/nersc_gnn_event_weights.py +++ b/dnn_reco/modules/data/event_weights/nersc_gnn_event_weights.py @@ -12,7 +12,7 @@ An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -47,7 +47,7 @@ def nersc_gnn_weight( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. diff --git a/dnn_reco/modules/data/labels/biased_selection_labels.py b/dnn_reco/modules/data/labels/biased_selection_labels.py index 63f0ddc..b5fdbc2 100644 --- a/dnn_reco/modules/data/labels/biased_selection_labels.py +++ b/dnn_reco/modules/data/labels/biased_selection_labels.py @@ -11,7 +11,7 @@ label_names : None, optional The names of the labels. This defines which labels to include as well as the ordering. - If label_names is None (e.g. first call to initate name list), then + If label_names is None (e.g. first call to initiate name list), then a list of label names needs to be created and returned. *args Variable length argument list. @@ -34,7 +34,7 @@ def biased_muongun(input_data, config, label_names=None, *args, **kwargs): - """Default muon scattering labels in addtion to relaxed thresholds for + """Default muon scattering labels in addition to relaxed thresholds for classification. Parameters diff --git a/dnn_reco/modules/data/labels/default_labels.py b/dnn_reco/modules/data/labels/default_labels.py index 42888e8..9443189 100644 --- a/dnn_reco/modules/data/labels/default_labels.py +++ b/dnn_reco/modules/data/labels/default_labels.py @@ -11,7 +11,7 @@ label_names : None, optional The names of the labels. This defines which labels to include as well as the ordering. - If label_names is None (e.g. first call to initate name list), then + If label_names is None (e.g. first call to initiate name list), then a list of label names needs to be created and returned. *args Variable length argument list. diff --git a/dnn_reco/modules/data/labels/event_selection_labels.py b/dnn_reco/modules/data/labels/event_selection_labels.py index 9644273..71fdf64 100644 --- a/dnn_reco/modules/data/labels/event_selection_labels.py +++ b/dnn_reco/modules/data/labels/event_selection_labels.py @@ -11,7 +11,7 @@ label_names : None, optional The names of the labels. This defines which labels to include as well as the ordering. - If label_names is None (e.g. first call to initate name list), then + If label_names is None (e.g. first call to initiate name list), then a list of label names needs to be created and returned. *args Variable length argument list. @@ -171,7 +171,7 @@ def starting_cascades(input_data, config, label_names=None, *args, **kwargs): else: distances = [-60.0, 0.0, 60, 300.0, float("inf")] - # make sure the provdied distances are allowed + # make sure the provided distances are allowed allowed_distances = [-60.0, 0.0, 60, 150.0, 300.0, float("inf")] assert np.all([d in allowed_distances for d in distances]), distances diff --git a/dnn_reco/modules/data/labels/muon_scattering_labels.py b/dnn_reco/modules/data/labels/muon_scattering_labels.py index 42afd3c..0ff3453 100644 --- a/dnn_reco/modules/data/labels/muon_scattering_labels.py +++ b/dnn_reco/modules/data/labels/muon_scattering_labels.py @@ -11,7 +11,7 @@ label_names : None, optional The names of the labels. This defines which labels to include as well as the ordering. - If label_names is None (e.g. first call to initate name list), then + If label_names is None (e.g. first call to initiate name list), then a list of label names needs to be created and returned. *args Variable length argument list. @@ -34,7 +34,7 @@ def muon_scattering(input_data, config, label_names=None, *args, **kwargs): - """Default muon scattering labels in addtion to relaxed thresholds for + """Default muon scattering labels in addition to relaxed thresholds for classification. Parameters diff --git a/dnn_reco/modules/data/misc/default_misc.py b/dnn_reco/modules/data/misc/default_misc.py index b67497d..3b66861 100644 --- a/dnn_reco/modules/data/misc/default_misc.py +++ b/dnn_reco/modules/data/misc/default_misc.py @@ -11,7 +11,7 @@ misc_names : None, optional The names of the misc variables. This defines which variables to include as well as the ordering. - If misc_names is None (e.g. first call to initate name list), then + If misc_names is None (e.g. first call to initiate name list), then a list of misc names needs to be created and returned. *args Variable length argument list. @@ -47,7 +47,7 @@ def dummy_misc_loader(input_data, config, misc_names=None, *args, **kwargs): misc_names : None, optional The names of the misc variables. This defines which variables to include as well as the ordering. - If misc_names is None (e.g. first call to initate name list), then + If misc_names is None (e.g. first call to initiate name list), then a list of misc names needs to be created and returned. *args Variable length argument list. @@ -78,7 +78,7 @@ def general_misc_loader(input_data, config, misc_names=None, *args, **kwargs): misc_names : None, optional The names of the misc variables. This defines which variables to include as well as the ordering. - If misc_names is None (e.g. first call to initate name list), then + If misc_names is None (e.g. first call to initiate name list), then a list of misc names needs to be created and returned. *args Variable length argument list. diff --git a/dnn_reco/modules/evaluation/default_evaluation.py b/dnn_reco/modules/evaluation/default_evaluation.py index 277e0b4..e96a718 100644 --- a/dnn_reco/modules/evaluation/default_evaluation.py +++ b/dnn_reco/modules/evaluation/default_evaluation.py @@ -24,7 +24,7 @@ An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -75,7 +75,7 @@ def eval_direction( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -178,7 +178,7 @@ def eval_direction( ) ) - # Test weighted corection: [very much beta version] + # Test weighted correction: [very much beta version] def get_weighted_normed_dir_vector( dir_x, dir_y, dir_z, dir_x_unc, dir_y_unc, dir_z_unc ): diff --git a/dnn_reco/modules/loss/default_loss.py b/dnn_reco/modules/loss/default_loss.py index 9d0f56c..484eefe 100644 --- a/dnn_reco/modules/loss/default_loss.py +++ b/dnn_reco/modules/loss/default_loss.py @@ -12,7 +12,7 @@ An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -55,7 +55,7 @@ def weighted_mse( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -111,7 +111,7 @@ def mse( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -174,7 +174,7 @@ def abs( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -238,7 +238,7 @@ def gaussian_likelihood( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -303,7 +303,7 @@ def pull_distribution_scale( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -371,7 +371,7 @@ def mse_and_cross_entropy( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -466,7 +466,7 @@ def mse_and_weighted_cross_entropy( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -575,7 +575,7 @@ def tukey( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -642,7 +642,7 @@ def opening_angle( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -730,7 +730,7 @@ def opening_angle_raleigh( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. diff --git a/dnn_reco/modules/loss/track_loss.py b/dnn_reco/modules/loss/track_loss.py index d2b6c54..1532e32 100644 --- a/dnn_reco/modules/loss/track_loss.py +++ b/dnn_reco/modules/loss/track_loss.py @@ -12,7 +12,7 @@ An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -55,7 +55,7 @@ def track_pos_mse( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -114,7 +114,7 @@ def track_pos_mse( # scalar product s = a*d, s is distance to closest point on infinite track s = a1 * dir_x_true + a2 * dir_y_true + a3 * dir_z_true - # caculate r = s*d -a = (p + s*d) - x + # calculate r = s*d -a = (p + s*d) - x r1 = s * dir_x_true - a1 r2 = s * dir_y_true - a2 r3 = s * dir_z_true - a3 @@ -209,7 +209,7 @@ def track_pos_gaussian( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -268,7 +268,7 @@ def track_pos_gaussian( # scalar product s = a*d, s is distance to closest point on infinite track s = a1 * dir_x_true + a2 * dir_y_true + a3 * dir_z_true - # caculate r = s*d -a = (p + s*d) - x + # calculate r = s*d -a = (p + s*d) - x r1 = s * dir_x_true - a1 r2 = s * dir_y_true - a2 r3 = s * dir_z_true - a3 diff --git a/dnn_reco/modules/loss/utils/loss_utils.py b/dnn_reco/modules/loss/utils/loss_utils.py index b4c1775..22ceada 100644 --- a/dnn_reco/modules/loss/utils/loss_utils.py +++ b/dnn_reco/modules/loss/utils/loss_utils.py @@ -10,7 +10,7 @@ def add_logging_info(data_handler, shared_objects): - """Add some TensorBoard logging infor for the labels. + """Add some TensorBoard logging info for the labels. Adds Tf.summary.scalars of the RMSE for each label. @@ -20,7 +20,7 @@ def add_logging_info(data_handler, shared_objects): An instance of the DataHandler class. The object is used to obtain meta data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. """ @@ -32,7 +32,7 @@ def add_logging_info(data_handler, shared_objects): mse_values = tf.reduce_mean(input_tensor=tf.square(y_diff), axis=0) rmse_values = tf.sqrt(mse_values) - # calcuate RMSE of transformed values + # calculate RMSE of transformed values y_diff_trafo = ( shared_objects["y_pred_trafo"] - shared_objects["y_true_trafo"] ) @@ -136,7 +136,7 @@ def get_y_diff_trafo(config, data_handler, data_transformer, shared_objects): An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. Returns diff --git a/dnn_reco/modules/models/general_IC86_models.py b/dnn_reco/modules/models/general_IC86_models.py index 27f8f1a..3d3d307 100644 --- a/dnn_reco/modules/models/general_IC86_models.py +++ b/dnn_reco/modules/models/general_IC86_models.py @@ -14,7 +14,7 @@ An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -74,7 +74,7 @@ def general_model_IC86( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. @@ -357,7 +357,7 @@ def general_model_IC86_opt4( An instance of the DataTransformer class. The object is used to transform data. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. *args Variable length argument list. diff --git a/dnn_reco/modules/models/utils/model_utils.py b/dnn_reco/modules/models/utils/model_utils.py index a07ad3f..0a3efdb 100644 --- a/dnn_reco/modules/models/utils/model_utils.py +++ b/dnn_reco/modules/models/utils/model_utils.py @@ -18,7 +18,7 @@ def preprocess_icecube_data(is_training, shared_objects): is_training : bool True if model is in training mode, false if in inference mode. shared_objects : dict - A dictionary containg settings and objects that are shared and passed + A dictionary containing settings and objects that are shared and passed on to sub modules. Returns diff --git a/dnn_reco/setup_manager.py b/dnn_reco/setup_manager.py index 4b39097..3e469c7 100644 --- a/dnn_reco/setup_manager.py +++ b/dnn_reco/setup_manager.py @@ -58,7 +58,7 @@ class SetupManager: The shape of the DOM response tensor excluding the batch dimension. E.g.: [x_dim, y_dim, z_dim, num_bins] DOM_init_values: float or array-like - The x_ic78 and deepcore array will be initalized with these + The x_ic78 and deepcore array will be initialized with these values via: np.zeros_like(x_ic78) * np.array(init_values) batch_size : int @@ -111,7 +111,7 @@ class SetupManager: specified by the 'trafo_data' key. trafo_save_model : bool If true, the transformation model will be saved to the file - specfied by the 'trafo_model_path' key. + specified by the 'trafo_model_path' key. Note: This will overwrite the file! trafo_normalize : bool If true, data will be normalized to have a mean of 0 and a variance @@ -172,7 +172,7 @@ class SetupManager: config : dictionary Dictionary with defined settings. shared_objects : dictionary - Dictionary with additional objects that are availabe in all modules. + Dictionary with additional objects that are available in all modules. Keys: 'data_transformer' : DataTransformer object used to transform data. 'keep_prob_list' : Tensorflow placeholders for keep probabilities diff --git a/docs/source/pages/bootcamp.rst b/docs/source/pages/bootcamp.rst index fcc09d7..47ee4ec 100644 --- a/docs/source/pages/bootcamp.rst +++ b/docs/source/pages/bootcamp.rst @@ -10,7 +10,7 @@ IceCube DNN Bootcamp ******************** -This tutorial is a simplifed version of the :ref:`Getting Started tutorial` +This tutorial is a simplified version of the :ref:`Getting Started tutorial` where we will focus on: diff --git a/docs/source/pages/bootcamp/00_bootcamp_setup.rst b/docs/source/pages/bootcamp/00_bootcamp_setup.rst index e71aff3..d0d42c5 100644 --- a/docs/source/pages/bootcamp/00_bootcamp_setup.rst +++ b/docs/source/pages/bootcamp/00_bootcamp_setup.rst @@ -102,7 +102,7 @@ We are now ready to install the necessary prerequisites and |dnn_reco|. git clone https://github.com/mhuen/dnn_reco.git # make sure that your virtualenv is activated - # you can check this by exectuting + # you can check this by executing which pip # It should point to: echo ${DNN_HOME}/dnn_reco_env/bin/pip diff --git a/docs/source/pages/bootcamp/01_bootcamp_train.rst b/docs/source/pages/bootcamp/01_bootcamp_train.rst index 5bfb717..fe25d66 100644 --- a/docs/source/pages/bootcamp/01_bootcamp_train.rst +++ b/docs/source/pages/bootcamp/01_bootcamp_train.rst @@ -96,7 +96,7 @@ We are going to highlight a few options in the following: Path to which the transformation model will be saved. ``trafo_normalize_dom_data``/ ``trafo_normalize_label_data``/ ``trafo_normalize_misc_data``: - If true, the input data per DOM, labels, and miscellanous data will be + If true, the input data per DOM, labels, and miscellaneous data will be normalized to have a mean of zero and a standard deviation of one. ``trafo_log_dom_bins``: @@ -130,7 +130,7 @@ because the mean and standard deviation depend on the data. # create the transformation Model python create_trafo_model.py $CONFIG_DIR/getting_started.yaml -Upon succesful completion this should print: +Upon successful completion this should print: .. code-block:: php @@ -197,7 +197,7 @@ For now we will use a simple Mean Squared Error (MSE) for the prediction and uncertainty estimate. The structure of the setting ``model_optimizer_dict`` is a bit complicated, but it is very powerful. -We can define as many optimizers with as many loss funtions as we like. +We can define as many optimizers with as many loss functions as we like. A few basic loss functions are already implemented in ``dnn_reco.modules.loss``. You are free to add your custom loss functions by adding a file/function in @@ -231,7 +231,7 @@ This means that you do not have to keep track yourself. Moreover, the currently installed python packages and the git revision is logged. This information will be exported together with the model, to ensure -reproducability. +reproducibility. The keys ``model_checkpoint_path`` and ``log_path`` define where the model checkpoints and the tensorboard log files will be saved to. The ``model_checkpoint_path`` also defines the path from which the weights of @@ -251,5 +251,5 @@ each of your models. Therefore you can easily swap out modules and create custom ones. We have briefly touched the option to create your own neural network architecture here as well as the option to add custom loss functions. - More information on the exchangable modules is provided in + More information on the exchangeable modules is provided in :ref:`Code Documentation`. diff --git a/docs/source/pages/bootcamp/02_bootcamp_monitor.rst b/docs/source/pages/bootcamp/02_bootcamp_monitor.rst index ba48246..5a45171 100644 --- a/docs/source/pages/bootcamp/02_bootcamp_monitor.rst +++ b/docs/source/pages/bootcamp/02_bootcamp_monitor.rst @@ -35,7 +35,7 @@ The input pipeline consists of three steps: 2. Another worker aggregates the events of several files (number of files defined by ``num_add_files``) together - by dequeing elements from the 'data_batch_queue'. + by dequeuing elements from the 'data_batch_queue'. It then creates batches from these events (randomly if 'sample_randomly' == True ). These batches are then put onto the 'final_batch_queue'. @@ -102,7 +102,7 @@ We can then use tensorboard to render these logs. # to forward this port in the ssh connection tensorboard --logdir=PATH/TO/MY/LOGS --port 7475 -If the port forwading is correctly set up, you can then point your browser to +If the port forwarding is correctly set up, you can then point your browser to to the appropriate address. More info on tensorboard is provided here: https://www.tensorflow.org/guide/summaries_and_tensorboard. diff --git a/docs/source/pages/bootcamp/03_bootcamp_apply.rst b/docs/source/pages/bootcamp/03_bootcamp_apply.rst index d508c37..5e56b68 100644 --- a/docs/source/pages/bootcamp/03_bootcamp_apply.rst +++ b/docs/source/pages/bootcamp/03_bootcamp_apply.rst @@ -107,7 +107,7 @@ following: model_names = [str(model_names)] output_names = ["DeepLearningReco_{}".format(m) for m in model_names] - # Make sure DNN reco will be writen to hdf5 file + # Make sure DNN reco will be written to hdf5 file for outbox in output_names: if outbox not in HDF_keys: HDF_keys.append(outbox) diff --git a/docs/source/pages/code.rst b/docs/source/pages/code.rst index cdcfe12..c3abdee 100644 --- a/docs/source/pages/code.rst +++ b/docs/source/pages/code.rst @@ -18,8 +18,8 @@ IceCube Detector Specifics .. automodule:: dnn_reco.detector :members: -Miscellanous Module -=================== +Miscellaneous Module +==================== .. automodule:: dnn_reco.misc :members: @@ -51,8 +51,8 @@ Loss Functions .. automodule:: dnn_reco.modules.loss.utils.loss_utils :members: -Evalution Functions -=================== +Evaluation Functions +==================== .. automodule:: dnn_reco.modules.evaluation.default_evaluation :members: diff --git a/docs/source/pages/config.rst b/docs/source/pages/config.rst index 9cfedb7..f51991b 100644 --- a/docs/source/pages/config.rst +++ b/docs/source/pages/config.rst @@ -32,7 +32,7 @@ General Settings validation set. ``test_data_file``: - If the data handler object is not instanciated with a config, it will load + If the data handler object is not instantiated with a config, it will load one of these files to obtain meta data, such as the labels and misc data names. @@ -352,7 +352,7 @@ Trafo Settings Path to which the transformation model will be saved. ``trafo_normalize_dom_data``/ ``trafo_normalize_label_data``/ ``trafo_normalize_misc_data``: - If true, the input data per DOM, labels, and miscellanous data will be + If true, the input data per DOM, labels, and miscellaneous data will be normalized to have a mean of zero and a standard deviation of one. ``trafo_log_dom_bins``: @@ -447,7 +447,7 @@ NN Model Architecture The network architecture that will be used is defined by the ``model_file`` and ``model_name`` keys. The ``model_name`` defines the function that will be used to - create and buld the model. + create and build the model. Default: `general_model_IC86` ``model_is_training``: diff --git a/docs/source/pages/getting_started/01_create_training_data.rst b/docs/source/pages/getting_started/01_create_training_data.rst index ac7ff37..635e847 100644 --- a/docs/source/pages/getting_started/01_create_training_data.rst +++ b/docs/source/pages/getting_started/01_create_training_data.rst @@ -10,14 +10,14 @@ Create Training Data ******************** To create the training data we will use the tray -segment ``ic3_data.segements.CreateDNNData`` from the |ic3_data| project +segment ``ic3_data.segments.CreateDNNData`` from the |ic3_data| project and for the labels we will use ``ic3_labels.labels.modules.MCLabelsCascades`` from the |ic3_labels| repository. You are free to include these modules in your processing set up of choice. Here we will use `these processing scripts `_. -The tray segment ``ic3_data.segements.CreateDNNData`` can write out different +The tray segment ``ic3_data.segments.CreateDNNData`` can write out different types of input data. Options include (more available): @@ -29,7 +29,7 @@ Options include (more available): If your application needs different input data, you can easily add a function in ``ic3_data.data_formats``. -The 'DataFormat' key of the tray segment ``ic3_data.segements.CreateDNNData`` +The 'DataFormat' key of the tray segment ``ic3_data.segments.CreateDNNData`` defines which function in ``ic3_data.data_formats`` will be used to create the input data. The only requirement is that the input data must be a vector of length n for @@ -155,7 +155,7 @@ Create the job files via: # create job files (--help for more options) python create_job_files.py configs/tutorial_dnn_reco/getting_started/create_training_data_01_py3-v4.1.1.yaml -d $DNN_HOME/training_data/ -This will write the exectuable job files and the configuration file that was used +This will write the executable job files and the configuration file that was used to the directory ``$DNN_HOME/training_data/processing``. The output files will be written to ``$DNN_HOME/training_data/datasets``. You may also write DAGMan files if you pass the option ``--dagman``. diff --git a/docs/source/pages/getting_started/02_train_model.rst b/docs/source/pages/getting_started/02_train_model.rst index ba9da73..c5322d6 100644 --- a/docs/source/pages/getting_started/02_train_model.rst +++ b/docs/source/pages/getting_started/02_train_model.rst @@ -138,7 +138,7 @@ We are going to highlight a few options in the following: Path to which the transformation model will be saved. ``trafo_normalize_dom_data``/ ``trafo_normalize_label_data``/ ``trafo_normalize_misc_data``: - If true, the input data per DOM, labels, and miscellanous data will be + If true, the input data per DOM, labels, and miscellaneous data will be normalized to have a mean of zero and a standard deviation of one. ``trafo_log_dom_bins``: @@ -183,7 +183,7 @@ because the mean and standard deviation depend on the data. ``$CONFIG_DIR/getting_started.yaml`` to a lower value such as 20. -Upon succesful completion this should print: +Upon successful completion this should print: .. code-block:: php @@ -243,7 +243,7 @@ in the ``model_optimizer_dict``. Here, we will use a Gaussian Likelihood as the loss function for the prediction and uncertainty estimate. The structure of the setting ``model_optimizer_dict`` is a bit complicated, but it is very powerful. -We can define as many optimizers with as many loss funtions as we like. +We can define as many optimizers with as many loss functions as we like. A few basic loss functions are already implemented in ``dnn_reco.modules.loss``. Amongst others, these include the Mean Squared Error (MSE) and cross-entropy @@ -302,7 +302,7 @@ This means that you do not have to keep track yourself. Moreover, the currently installed python packages and the git revision is logged. This information will be exported together with the model, to ensure -reproducability. +reproducibility. The keys ``model_checkpoint_path`` and ``log_path`` define where the model checkpoints and the tensorboard log files will be saved to. The ``model_checkpoint_path`` also defines the path from which the weights of @@ -322,7 +322,7 @@ each of your models. Therefore you can easily swap out modules and create custom ones. We have briefly touched the option to create your own neural network architecture here as well as the option to add custom loss functions. - More information on the exchangable modules is provided in + More information on the exchangeable modules is provided in :ref:`Code Documentation`. diff --git a/docs/source/pages/getting_started/03_monitor_progress.rst b/docs/source/pages/getting_started/03_monitor_progress.rst index fa51968..07afaf3 100644 --- a/docs/source/pages/getting_started/03_monitor_progress.rst +++ b/docs/source/pages/getting_started/03_monitor_progress.rst @@ -35,7 +35,7 @@ The input pipeline consists of three steps: 2. Another worker aggregates the events of several files (number of files defined by ``num_add_files``) together - by dequeing elements from the 'data_batch_queue'. + by dequeuing elements from the 'data_batch_queue'. It then creates batches from these events (randomly if 'sample_randomly' == True ). These batches are then put onto the 'final_batch_queue'. @@ -102,7 +102,7 @@ We can then use tensorboard to render these logs. # to forward this port in the ssh connection tensorboard --logdir=PATH/TO/MY/LOGS --port 7475 -If the port forwading is correctly set up, you can then point your browser to +If the port forwarding is correctly set up, you can then point your browser to to the appropriate address. More info on tensorboard is provided here: https://www.tensorflow.org/guide/summaries_and_tensorboard. diff --git a/docs/source/pages/getting_started/04_apply_model.rst b/docs/source/pages/getting_started/04_apply_model.rst index 62a0688..ff0203e 100644 --- a/docs/source/pages/getting_started/04_apply_model.rst +++ b/docs/source/pages/getting_started/04_apply_model.rst @@ -110,7 +110,7 @@ following: model_names = [str(model_names)] output_names = ["DeepLearningReco_{}".format(m) for m in model_names] - # Make sure DNN reco will be writen to hdf5 file + # Make sure DNN reco will be written to hdf5 file for outbox in output_names: if outbox not in HDF_keys: HDF_keys.append(outbox) diff --git a/docs/source/pages/installation.rst b/docs/source/pages/installation.rst index 429e537..b0c9a2f 100644 --- a/docs/source/pages/installation.rst +++ b/docs/source/pages/installation.rst @@ -71,7 +71,7 @@ directories to find packages before it looks inside the virtual environment. We want to avoid this and enforce that packages from our virtual environment are used first. To do this we need to prepend the path to our virtual environment in the ``$PYTHONPATH``. Since we don't want to do this manually -everytime we load the environment, we can add this to the ``activate`` shell +every time we load the environment, we can add this to the ``activate`` shell script that starts the virtual environment. We will need to add the following to the ``deactivate ()`` function @@ -111,7 +111,7 @@ pip is being used, you can execute the following. .. code-block:: bash # make sure that your virtualenv is activated - # you can check this by exectuting + # you can check this by executing which pip # It should point to: echo ${DNN_HOME}/py3-v4.1.1_tensorflow2.3/bin/pip diff --git a/docs/source/pages/models.rst b/docs/source/pages/models.rst index ae73f05..e4018ad 100644 --- a/docs/source/pages/models.rst +++ b/docs/source/pages/models.rst @@ -32,7 +32,7 @@ If run on a CPU, the number of CPUs to run the model on may be passed via ``num_cpus``. Especially if on a GPU, it is advisable to run the |dnn_reco| on batches of events at a time. This can be controlled via ``batch_size`` which defines the -number of events to reconstruct simulatenously. +number of events to reconstruct simulateneously. The best settings depend on the hardware setup. A good staring point could be 32 or 64. diff --git a/pyproject.toml b/pyproject.toml index 84d5b01..56a99cf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -81,5 +81,8 @@ lint.ignore = [ line-length = 79 target-version = "py38" +[tool.codespell] +ignore-words-list = "hese,mese,livetime" + [tool.ruff.lint.pydocstyle] convention = "numpy" diff --git a/tests_manual/test.py b/tests_manual/test.py index c632817..6034e8c 100644 --- a/tests_manual/test.py +++ b/tests_manual/test.py @@ -78,10 +78,10 @@ def error(msg): rtol=5e-4, ): if key == "LabelsDeepLearning": - warning("\t\tWarning: mis-match for {}".format(k)) + warning("\t\tWarning: mismatch for {}".format(k)) got_warning = True else: - error("\t\tError: mis-match for {}".format(k)) + error("\t\tError: mismatch for {}".format(k)) passed_test = False print( "\t\t",