|
4399 | 4399 | }, |
4400 | 4400 | { |
4401 | 4401 | "cell_type": "code", |
4402 | | - "execution_count": 4, |
| 4402 | + "execution_count": null, |
4403 | 4403 | "metadata": {}, |
4404 | 4404 | "outputs": [], |
4405 | 4405 | "source": [ |
|
4418 | 4418 | }, |
4419 | 4419 | { |
4420 | 4420 | "cell_type": "code", |
4421 | | - "execution_count": 2, |
| 4421 | + "execution_count": null, |
4422 | 4422 | "metadata": {}, |
4423 | 4423 | "outputs": [], |
4424 | 4424 | "source": [ |
|
4453 | 4453 | }, |
4454 | 4454 | { |
4455 | 4455 | "cell_type": "code", |
4456 | | - "execution_count": 6, |
| 4456 | + "execution_count": null, |
4457 | 4457 | "metadata": {}, |
4458 | 4458 | "outputs": [], |
4459 | 4459 | "source": [ |
|
4470 | 4470 | }, |
4471 | 4471 | { |
4472 | 4472 | "cell_type": "code", |
4473 | | - "execution_count": 8, |
| 4473 | + "execution_count": null, |
4474 | 4474 | "metadata": {}, |
4475 | 4475 | "outputs": [], |
4476 | 4476 | "source": [ |
|
4486 | 4486 | }, |
4487 | 4487 | { |
4488 | 4488 | "cell_type": "code", |
4489 | | - "execution_count": 10, |
| 4489 | + "execution_count": null, |
4490 | 4490 | "metadata": {}, |
4491 | 4491 | "outputs": [], |
4492 | 4492 | "source": [ |
|
4502 | 4502 | }, |
4503 | 4503 | { |
4504 | 4504 | "cell_type": "code", |
4505 | | - "execution_count": 2, |
| 4505 | + "execution_count": null, |
4506 | 4506 | "metadata": {}, |
4507 | 4507 | "outputs": [], |
4508 | 4508 | "source": [ |
|
4512 | 4512 | "data.frame.to_csv('iris.csv', index=False)\n" |
4513 | 4513 | ] |
4514 | 4514 | }, |
| 4515 | + { |
| 4516 | + "cell_type": "code", |
| 4517 | + "execution_count": null, |
| 4518 | + "metadata": {}, |
| 4519 | + "outputs": [], |
| 4520 | + "source": [ |
| 4521 | + "from spotGUI.tuner.spotRun import get_report_file_name\n", |
| 4522 | + "from spotPython.utils.init import fun_control_init\n", |
| 4523 | + "fun_control = fun_control_init(PREFIX=\"test\")\n", |
| 4524 | + "get_report_file_name(fun_control)" |
| 4525 | + ] |
| 4526 | + }, |
| 4527 | + { |
| 4528 | + "cell_type": "code", |
| 4529 | + "execution_count": null, |
| 4530 | + "metadata": {}, |
| 4531 | + "outputs": [], |
| 4532 | + "source": [ |
| 4533 | + "from spotGUI.tuner.spotRun import get_scenario_dict\n", |
| 4534 | + "import pprint\n", |
| 4535 | + "dic = get_scenario_dict(\"sklearn\")\n", |
| 4536 | + "pprint.pprint(dic)" |
| 4537 | + ] |
| 4538 | + }, |
| 4539 | + { |
| 4540 | + "cell_type": "code", |
| 4541 | + "execution_count": 5, |
| 4542 | + "metadata": {}, |
| 4543 | + "outputs": [ |
| 4544 | + { |
| 4545 | + "name": "stdout", |
| 4546 | + "output_type": "stream", |
| 4547 | + "text": [ |
| 4548 | + "Selected messreihen: ['MR001A', 'MR001H', 'MR001aH', 'MR001bH', 'MR001cH', 'MR001dH', 'MR001eH', 'MR001vH', 'MR001wH', 'MR002aH', 'MR002bH', 'MR002cH', 'MR002dH', 'MR002eH', 'MR003aH', 'MR003bH', 'MR003cH', 'MR003dH', 'MR003eH', 'MR003fH', 'MR003gH', 'MR02H', 'MR02bH', 'MR02cH', 'MR02dH', 'MR02zA', 'MR02zH', 'MR03A', 'MR03H', 'MR03aH', 'MR03bH', 'MR03cH', 'MR03dH', 'MR04A', 'MR04H', 'MR04aH', 'MR04cH', 'MR04dH', 'MR04eH', 'MR05A', 'MR05H', 'MR05aH', 'MR05bH', 'MR05cH', 'MR05dH', 'MR05eH']\n", |
| 4549 | + "Loading data for ['C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'N', 'U', 'V', 'W', 'X', 'Y', 'AS', 'AT', 'AV', 'AW', 'AX', 'AZ', 'BA', 'BB', 'BC', 'BD', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BP', 'BQ', 'BR', 'BS', 'BU', 'BV', 'BW', 'BX', 'BY', 'BZ', 'CA', 'CB', 'CD', 'CE', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CO', 'CP', 'CQ', 'CR', 'CS', 'CT', 'CU', 'CV', 'CW', 'CX', 'CY', 'CZ', 'DA', 'DB', 'DC', 'DD', 'DE', 'DG', 'DH', 'DI', 'DJ', 'DK', 'DL', 'DM', 'DN', 'DP', 'DQ', 'DR', 'DS', 'DT', 'DU', 'DV']\n", |
| 4550 | + "Loaded df.columns: Index(['AS Drossel Drucks.', 'AT Drossel Saugs.', 'AV Drehzahl Verd', 'AW u2',\n", |
| 4551 | + " 'AX Drehzahl Motor', 'AZ p U', 'BA Umgebungsdruck Kontrolle',\n", |
| 4552 | + " 'BB p tot vV', 'BC p tot nV', 'BD Pi tot V', 'BF p Blende',\n", |
| 4553 | + " 'BG p_Blende B Kontrolle', 'BH p Blende BW', 'BI p_Blende BW Kontrolle',\n", |
| 4554 | + " 'BJ T Selbstlaufblende', 'BL V tot V red', 'BM m V red',\n", |
| 4555 | + " 'BN Reaktionsgrad V', 'BP rho vV', 'BQ rho nV', 'BR rel. Luftfeuchte',\n", |
| 4556 | + " 'BS T-Luftfeuchte', 'BU TvV_1', 'BV TvV_2', 'BW TvV_3', 'BX TvV_4',\n", |
| 4557 | + " 'BY TvV_5', 'BZ TvV_6', 'C Messreihe ', 'CA TvV_7', 'CB TvV_8',\n", |
| 4558 | + " 'CD TnV_1', 'CE TnV_2', 'CF TnV_3', 'CG TnV_4', 'CH TnV_5', 'CI TnV_6',\n", |
| 4559 | + " 'CK p Radseitenraum Verdichter', 'CL p_stat_SEALING-COVER_01',\n", |
| 4560 | + " 'CM p_stat_SEALING-COVER_02', 'CN p_stat_SEALING-COVER_03',\n", |
| 4561 | + " 'CO p_stat_SEALING-COVER_04', 'CP p_stat_SEALING-COVER_05',\n", |
| 4562 | + " 'CQ p_stat_SEALING-COVER_06', 'CR p_stat_SEALING-COVER_07',\n", |
| 4563 | + " 'CS p_stat_SEALING-COVER_08', 'CT p_stat_SEALING-COVER_09',\n", |
| 4564 | + " 'CU p_stat_SEALING-COVER_10', 'CV p_stat_SEALING-COVER_11',\n", |
| 4565 | + " 'CW p_stat_SEALING-COVER_12', 'CX p_stat_SEALING-COVER_13',\n", |
| 4566 | + " 'CY p_stat_SEALING-COVER_14', 'CZ p_stat_SEALING-COVER_15',\n", |
| 4567 | + " 'D Flächenverhältnis ', 'DA p_stat_SEALING-COVER_16',\n", |
| 4568 | + " 'DB p_stat_SEALING-COVER_17', 'DC p_stat_SEALING-COVER_18',\n", |
| 4569 | + " 'DD p_stat_SEALING-COVER_19', 'DE p_stat_SEALING-COVER_20', 'DG p Öl',\n", |
| 4570 | + " 'DH p Öl PLAG', 'DI p Öl TBOG', 'DJ T Öl ein', 'DK T Öl aus PLAG',\n", |
| 4571 | + " 'DL T Öl aus TBOG', 'DM T Öl aus VERD', 'DN Töl nach Tank',\n", |
| 4572 | + " 'DP T_Axiallager 1', 'DQ T_Axiallager 2', 'DR T_Axiallager 3',\n", |
| 4573 | + " 'DS T_Lager_3_Turbogetriebe_1', 'DT T_Lager_4_Turbogetriebe_1',\n", |
| 4574 | + " 'DU T_Lager_3_Turbogetriebe_2', 'DV T_Lager_4_Turbogetriebe_2',\n", |
| 4575 | + " 'E Drosselstellung ', 'F DMS ', 'G Zeit [s]', 'H Drehzahl [1/min]',\n", |
| 4576 | + " 'I Ordnung []', 'J Frequenz [Hz]', 'K Knotendurchmesser []',\n", |
| 4577 | + " 'L Mode []', 'N AufgewAmplitudeNom [MPa]', 'U Sensitivität []',\n", |
| 4578 | + " 'V Güteklasse []', 'W ex_ey []', 'X Sx_ex_E []', 'Y Krümmung []'],\n", |
| 4579 | + " dtype='object')\n", |
| 4580 | + "non_numerical_columns before encoding: C Messreihe F DMS \n", |
| 4581 | + "0 MR001A HS5-M3S\n", |
| 4582 | + "1 MR001A HS5-M2D\n", |
| 4583 | + "2 MR001A HS9-M3S\n", |
| 4584 | + "3 MR05A HS5-M3S\n", |
| 4585 | + "4 MR05A HS5-M2D\n", |
| 4586 | + "... ... ...\n", |
| 4587 | + "27855 MR02zH HS5-M2D\n", |
| 4588 | + "27856 MR02zH HS5-M2D\n", |
| 4589 | + "27857 MR02zH HS9-M3S\n", |
| 4590 | + "27858 MR02zH HS5-M2D\n", |
| 4591 | + "27859 MR02zH HS5-M2D\n", |
| 4592 | + "\n", |
| 4593 | + "[27857 rows x 2 columns]\n", |
| 4594 | + "non_numerical_columns after encoding: C Messreihe F DMS \n", |
| 4595 | + "0 0.0 1.0\n", |
| 4596 | + "1 0.0 0.0\n", |
| 4597 | + "2 0.0 4.0\n", |
| 4598 | + "3 39.0 1.0\n", |
| 4599 | + "4 39.0 0.0\n", |
| 4600 | + "... ... ...\n", |
| 4601 | + "27855 26.0 0.0\n", |
| 4602 | + "27856 26.0 0.0\n", |
| 4603 | + "27857 26.0 4.0\n", |
| 4604 | + "27858 26.0 0.0\n", |
| 4605 | + "27859 26.0 0.0\n", |
| 4606 | + "\n", |
| 4607 | + "[27857 rows x 2 columns]\n", |
| 4608 | + "<class 'torch.utils.data.dataset.TensorDataset'>\n", |
| 4609 | + "27857\n" |
| 4610 | + ] |
| 4611 | + } |
| 4612 | + ], |
| 4613 | + "source": [ |
| 4614 | + "from pyhcf.utils.io import load_hcf_dataframe, hcf_df2tensor\n", |
| 4615 | + "from pyhcf.utils.names import load_all_features_N_regression_list\n", |
| 4616 | + "from torch.utils.data import DataLoader\n", |
| 4617 | + "df = load_hcf_dataframe(A=True,\n", |
| 4618 | + " H=True,\n", |
| 4619 | + " param_list=load_all_features_N_regression_list(),\n", |
| 4620 | + " target='N',\n", |
| 4621 | + " rmNA=True,\n", |
| 4622 | + " rmMF=True,\n", |
| 4623 | + " rmV=4,\n", |
| 4624 | + " min_freq=1000,\n", |
| 4625 | + " incl_drossel=False)\n", |
| 4626 | + "dataset = hcf_df2tensor(df, target='N', return_X_y=False)\n", |
| 4627 | + "print(type(dataset))\n", |
| 4628 | + "print(len(dataset))\n", |
| 4629 | + "# save the 'TensorDataset' object to a pkl file\n", |
| 4630 | + "# import pickle\n", |
| 4631 | + "# with open('hcf_dataset.pkl', 'wb') as f:\n", |
| 4632 | + "# pickle.dump(dataset, f)\n", |
| 4633 | + "# load the 'TensorDataset' object from the pkl file\n", |
| 4634 | + "# with open('hcf_dataset.pkl', 'rb') as f:\n", |
| 4635 | + "# dataset = pickle.load(f)" |
| 4636 | + ] |
| 4637 | + }, |
| 4638 | + { |
| 4639 | + "cell_type": "code", |
| 4640 | + "execution_count": 27, |
| 4641 | + "metadata": {}, |
| 4642 | + "outputs": [ |
| 4643 | + { |
| 4644 | + "data": { |
| 4645 | + "text/plain": [ |
| 4646 | + "86" |
| 4647 | + ] |
| 4648 | + }, |
| 4649 | + "execution_count": 27, |
| 4650 | + "metadata": {}, |
| 4651 | + "output_type": "execute_result" |
| 4652 | + } |
| 4653 | + ], |
| 4654 | + "source": [ |
| 4655 | + "dataset.__getitem__(0)\n", |
| 4656 | + "# get the dimensions of the first sample\n", |
| 4657 | + "dataset.__getitem__(0)[0].shape[0]" |
| 4658 | + ] |
| 4659 | + }, |
4515 | 4660 | { |
4516 | 4661 | "cell_type": "code", |
4517 | 4662 | "execution_count": null, |
|
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