CrbnsCat10n
484643409d
modified: checkpoints/forward/best_tcn_model.pt modified: checkpoints/forward/training_history.csv new file: checkpoints_mlp/task1_feature_mlp/best_feature_mlp.pt new file: checkpoints_mlp/task1_feature_mlp/training_history.csv new file: checkpoints_rms/forward_rms/best_rms_model.pt new file: checkpoints_rms/forward_rms/training_history.csv modified: evaluation_outputs/forward/evaluation_forward_test_b0_s0.png new file: evaluation_outputs/forward/evaluation_forward_val_b0_s0.png new file: evaluation_outputs/forward/evaluation_forward_val_b3_s0.png new file: evaluation_outputs/forward_rms/evaluation_test_all_samples.csv new file: evaluation_outputs/forward_rms/evaluation_test_s0.png new file: evaluation_outputs/forward_rms/evaluation_train_all_samples.csv new file: evaluation_outputs/forward_rms/evaluation_val_all_samples.csv new file: evaluation_outputs/forward_rms/evaluation_val_s0.png new file: evaluation_outputs/forward_rms/evaluation_val_s0_waveform.png new file: evaluation_outputs/task1_feature_mlp/evaluation_train_all_samples.csv new file: evaluation_outputs/task1_feature_mlp/evaluation_train_curve.png new file: evaluation_outputs/task1_feature_mlp/evaluation_val_all_samples.csv new file: evaluation_outputs/task1_feature_mlp/evaluation_val_curve.png new file: evaluation_outputs/task1_feature_mlp/evaluation_val_s0.png new file: evaluation_outputs/task1_feature_mlp/harmonic_5mm_0.75Hz_prediction.png new file: evaluation_outputs/task1_feature_mlp/harmonic_5mm_1.55Hz_prediction.png new file: scripts/__pycache__/config.cpython-310.pyc new file: scripts/__pycache__/dataset.cpython-310.pyc new file: scripts/__pycache__/model.cpython-310.pyc new file: scripts/config.py new file: scripts/dataset.py new file: scripts/evaluate.py new file: scripts/model.py new file: scripts/predict_single.py new file: scripts/train.py modified: src/__pycache__/config.cpython-310.pyc modified: src/__pycache__/dataset.cpython-310.pyc modified: src/__pycache__/model.cpython-310.pyc modified: src/config.py modified: src/dataset.py modified: src/model.py new file: src_new/__pycache__/config.cpython-310.pyc new file: src_new/__pycache__/dataset.cpython-310.pyc new file: src_new/__pycache__/evaluate.cpython-310.pyc new file: src_new/__pycache__/model.cpython-310.pyc new file: src_new/__pycache__/train.cpython-310.pyc new file: src_new/config.py new file: src_new/dataset.py new file: src_new/evaluate.py new file: src_new/model.py new file: src_new/train.py
2.5 KiB
2.5 KiB
| 1 | file_name | frequency_hz | true_rms | pred_rms | relative_error_percent | dominant_frequency_hz | frequency_squared | inverse_frequency_hz | log_frequency_hz | input_rms | input_peak_abs | input_peak_to_peak | crest_factor | middle_length_ratio | dominant_amplitude | dominant_energy_ratio | harmonic_fit_amplitude | harmonic_fit_residual_ratio | spectral_peak_prominence | half_power_bandwidth_hz | spectral_centroid_hz | signal_mean | sampling_rate |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2 | harmonic_5mm_1.85Hz.csv | 1.850000023841858 | 1.185911774635315 | 1.2428719997406006 | 4.803074421181267 | 1.8481981754302979 | 3.4158363342285156 | 0.5410675406455994 | 0.6142112016677856 | 0.6145902872085571 | 1.3770899772644043 | 2.6619200706481934 | 2.240663528442383 | 0.25 | 0.7274389863014221 | 0.9514397978782654 | 0.789516270160675 | 0.42080339789390564 | 85.657958984375 | 0.09677428752183914 | 1.8637527227401733 | -0.002481284085661173 | 50.000047683761295 |
| 3 | harmonic_5mm_1.25Hz.csv | 1.25 | 0.3802441656589508 | 0.4504010081291199 | 18.450471777414265 | 1.2483434677124023 | 1.5583614110946655 | 0.8010615706443787 | 0.22181743383407593 | 0.15971125662326813 | 0.5707299709320068 | 1.0413799285888672 | 3.5735113620758057 | 0.24992592632770538 | 0.1439778357744217 | 0.8661479949951172 | 0.14893445372581482 | 0.7513272762298584 | 56.41539764404297 | 0.05927687883377075 | 1.4980274438858032 | -0.0021986484061926603 | 50.000047683761295 |
| 4 | harmonic_5mm_0.95Hz.csv | 0.949999988079071 | 0.5053804516792297 | 0.3541945815086365 | 29.915258824959956 | 0.9513587951660156 | 0.9050835967063904 | 1.0511281490325928 | -0.04986399784684181 | 0.1381060928106308 | 0.5125100016593933 | 1.0134000778198242 | 3.7109878063201904 | 0.25 | 0.09424196928739548 | 0.7232213020324707 | 0.11362786591053009 | 0.8133426308631897 | 20.55999183654785 | 0.09677428752183914 | 1.3476505279541016 | 0.00015772903861943632 | 50.000047683761295 |
| 5 | harmonic_5mm_0.75Hz.csv | 0.75 | 0.39182430505752563 | 0.2595634460449219 | 33.755144156559126 | 0.7515671849250793 | 0.5648532509803772 | 1.3305530548095703 | -0.285594642162323 | 0.11687792837619781 | 0.4074699878692627 | 0.8070399761199951 | 3.4862868785858154 | 0.24992701411247253 | 0.10824807733297348 | 0.8746803998947144 | 0.11673416197299957 | 0.7099294662475586 | 36.5 | 0.08761690557003021 | 0.8937567472457886 | -0.001955104758962989 | 50.000047683761295 |
| 6 | harmonic_5mm_1.55Hz.csv | 1.5499999523162842 | 1.4177086353302002 | 0.9243398308753967 | 34.80043728025205 | 1.5492842197418213 | 2.4002816677093506 | 0.6454593539237976 | 0.4377930164337158 | 0.392645925283432 | 1.105049967765808 | 2.1589999198913574 | 2.8143677711486816 | 0.25 | 0.4746793210506439 | 0.9668325185775757 | 0.5014731884002686 | 0.43158969283103943 | 69.77510833740234 | 0.09836074709892273 | 1.584490418434143 | -0.0011147483019158244 | 50.000047683761295 |