Mercurial > repos > bgruening > sklearn_model_validation
annotate model_validation.xml @ 35:6c55d8a36f93 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
author | bgruening |
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date | Wed, 09 Aug 2023 13:59:46 +0000 |
parents | 1fe00785190d |
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1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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1 <tool id="sklearn_model_validation" name="Model Validation" version="@VERSION@" profile="@PROFILE@"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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2 <description>includes cross_validate, cross_val_predict, learning_curve, and more</description> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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3 <macros> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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4 <import>main_macros.xml</import> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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5 </macros> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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6 <expand macro="python_requirements" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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7 <expand macro="macro_stdio" /> |
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333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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8 <version_command>echo "@VERSION@"</version_command> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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9 <command> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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10 <![CDATA[ |
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5895fe0b8bde
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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11 export HDF5_USE_FILE_LOCKING='FALSE'; |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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12 python "$sklearn_model_validation_script" '$inputs' |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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13 ]]> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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14 </command> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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15 <configfiles> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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16 <inputs name="inputs" /> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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17 <configfile name="sklearn_model_validation_script"> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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18 <![CDATA[ |
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cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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19 import imblearn |
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efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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20 import joblib |
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333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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21 import json |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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22 import numpy as np |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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23 import os |
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cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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24 import pandas as pd |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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25 import pprint |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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26 import skrebate |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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27 import sys |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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28 import warnings |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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29 import xgboost |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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30 from mlxtend import classifier, regressor |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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31 from sklearn import ( |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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32 cluster, compose, decomposition, ensemble, feature_extraction, |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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33 feature_selection, gaussian_process, kernel_approximation, metrics, |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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34 model_selection, naive_bayes, neighbors, pipeline, preprocessing, |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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35 svm, linear_model, tree, discriminant_analysis) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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36 from sklearn.model_selection import _validation |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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37 from sklearn.preprocessing import LabelEncoder |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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38 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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39 from distutils.version import LooseVersion as Version |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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40 from galaxy_ml import __version__ as galaxy_ml_version |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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41 from galaxy_ml.model_persist import load_model_from_h5 |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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42 from galaxy_ml.utils import (SafeEval, get_cv, get_scoring, |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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43 read_columns, get_module, |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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44 clean_params, get_main_estimator) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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45 |
efbec977a47d
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46 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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47 N_JOBS = int(os.environ.get('GALAXY_SLOTS', 1)) |
a5aed87b2cc0
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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48 CACHE_DIR = os.path.join(os.getcwd(), 'cached') |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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49 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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50 warnings.filterwarnings('ignore') |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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51 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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52 safe_eval = SafeEval() |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 4ed8c4f6ef9ece81797a398b17a99bbaf49a6978
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53 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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54 input_json_path = sys.argv[1] |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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55 with open(input_json_path, 'r') as param_handler: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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56 params = json.load(param_handler) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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57 |
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58 ## load estimator |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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59 estimator = load_model_from_h5('$infile_estimator') |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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60 estimator = clean_params(estimator) |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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61 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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62 if estimator.__class__.__name__ == 'KerasGBatchClassifier': |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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63 _fit_and_score = try_get_attr('galaxy_ml.model_validations', |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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64 '_fit_and_score') |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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65 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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66 setattr(_search, '_fit_and_score', _fit_and_score) |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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67 setattr(_validation, '_fit_and_score', _fit_and_score) |
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68 |
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69 estimator_params = estimator.get_params() |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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70 |
efbec977a47d
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71 ## check estimator hyperparameters |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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72 memory = joblib.Memory(location=CACHE_DIR, verbose=0) |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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73 # cache iraps_core fits could increase search speed significantly |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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74 if estimator.__class__.__name__ == 'IRAPSClassifier': |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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75 estimator.set_params(memory=memory) |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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76 else: |
efbec977a47d
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77 # For iraps buried in pipeline |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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78 for p, v in estimator_params.items(): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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79 if p.endswith('__irapsclassifier__memory'): |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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80 new_params = {p: memory} |
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81 estimator.set_params(**new_params) |
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82 |
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83 ## store read dataframe object |
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84 loaded_df = {} |
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85 |
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86 #if $input_options.selected_input == 'tabular' |
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87 header = 'infer' if params['input_options']['header1'] else None |
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88 column_option = params['input_options']['column_selector_options_1']['selected_column_selector_option'] |
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89 if column_option in ['by_index_number', 'all_but_by_index_number', 'by_header_name', 'all_but_by_header_name']: |
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90 c = params['input_options']['column_selector_options_1']['col1'] |
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91 else: |
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92 c = None |
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93 infile1 = '$input_options.infile1' |
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94 df_key = infile1 + repr(header) |
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95 df = pd.read_csv(infile1, sep='\t', header=header, parse_dates=True) |
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96 loaded_df[df_key] = df |
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97 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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98 |
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99 #elif $input_options.selected_input == 'sparse': |
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100 X = mmread('$input_options.infile1') |
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101 |
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102 #elif $input_options.selected_input == 'seq_fasta' |
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103 fasta_path = '$input_options.fasta_path' |
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104 pyfaidx = get_module('pyfaidx') |
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105 sequences = pyfaidx.Fasta(fasta_path) |
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106 n_seqs = len(sequences.keys()) |
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107 X = np.arange(n_seqs)[:, np.newaxis] |
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108 for param in estimator_params.keys(): |
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109 if param.endswith('fasta_path'): |
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110 estimator.set_params( |
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111 **{param: fasta_path}) |
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112 break |
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113 else: |
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114 raise ValueError( |
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115 "The selected estimator doesn't support " |
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116 "fasta file input! Please consider using " |
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117 "KerasGBatchClassifier with " |
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118 "FastaDNABatchGenerator/FastaProteinBatchGenerator " |
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119 "or having GenomeOneHotEncoder/ProteinOneHotEncoder " |
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120 "in pipeline!") |
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121 #elif $input_options.selected_input == 'refseq_and_interval' |
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122 ref_seq = '$input_options.ref_genome_file' |
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123 intervals = '$input_options.interval_file' |
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124 targets = __import__('os').path.join(__import__('os').getcwd(), |
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125 '${target_file.element_identifier}.gz') |
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126 path_params = { |
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127 'data_batch_generator__ref_genome_path': ref_seq, |
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128 'data_batch_generator__intervals_path': intervals, |
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129 'data_batch_generator__target_path': targets |
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130 } |
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131 estimator.set_params(**path_params) |
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132 n_intervals = sum(1 for line in open(intervals)) |
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133 X = np.arange(n_intervals)[:, np.newaxis] |
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134 #end if |
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135 |
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136 header = 'infer' if params['input_options']['header2'] else None |
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137 column_option = params['input_options']['column_selector_options_2']['selected_column_selector_option2'] |
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138 if column_option in ['by_index_number', 'all_but_by_index_number', 'by_header_name', 'all_but_by_header_name']: |
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139 c = params['input_options']['column_selector_options_2']['col2'] |
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140 else: |
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141 c = None |
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142 infile2 = '$input_options.infile2' |
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143 df_key = infile2 + repr(header) |
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144 if df_key in loaded_df: |
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145 infile2 = loaded_df[df_key] |
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146 else: |
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147 infile2 = pd.read_csv(infile2, sep='\t', header=header, parse_dates=True) |
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148 loaded_df[df_key] = infile2 |
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149 y = read_columns( |
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150 infile2, |
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151 c = c, |
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152 c_option = column_option, |
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153 sep='\t', |
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154 header=header, |
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155 parse_dates=True) |
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156 if len(y.shape) == 2 and y.shape[1] == 1: |
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157 y = y.ravel() |
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158 #if $input_options.selected_input == 'refseq_and_interval' |
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159 estimator.set_params( |
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160 data_batch_generator__features=y.ravel().tolist()) |
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161 y = None |
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162 label_encoder = LabelEncoder() |
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163 if get_main_estimator(estimator).__class__.__name__ == "XGBClassifier": |
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164 y = label_encoder.fit_transform(y) |
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165 print(label_encoder.classes_) |
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166 #end if |
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167 |
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168 ## handle options |
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169 options = params['model_validation_functions']['options'] |
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170 |
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171 #if $model_validation_functions.options.cv_selector.selected_cv\ |
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172 in ['GroupKFold', 'GroupShuffleSplit', 'LeaveOneGroupOut', 'LeavePGroupsOut']: |
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173 infile_g = '$model_validation_functions.options.cv_selector.groups_selector.infile_g' |
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174 header = 'infer' if options['cv_selector']['groups_selector']['header_g'] else None |
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175 column_option = (options['cv_selector']['groups_selector']['column_selector_options_g'] |
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176 ['selected_column_selector_option_g']) |
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177 if column_option in ['by_index_number', 'all_but_by_index_number', |
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178 'by_header_name', 'all_but_by_header_name']: |
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179 c = (options['cv_selector']['groups_selector']['column_selector_options_g']['col_g']) |
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180 else: |
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181 c = None |
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182 df_key = infile_g + repr(header) |
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183 if df_key in loaded_df: |
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184 infile_g = loaded_df[df_key] |
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185 groups = read_columns(infile_g, c=c, c_option=column_option, |
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186 sep='\t', header=header, parse_dates=True) |
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187 groups = groups.ravel() |
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188 options['cv_selector']['groups_selector'] = groups |
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189 #end if |
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190 |
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191 ## del loaded_df |
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192 del loaded_df |
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193 |
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194 cv_selector = options.pop('cv_selector') |
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195 if Version(galaxy_ml_version) < Version('0.8.3'): |
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196 cv_selector.pop('n_stratification_bins', None) |
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197 splitter, groups = get_cv( cv_selector ) |
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198 options['cv'] = splitter |
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199 options['groups'] = groups |
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200 options['n_jobs'] = N_JOBS |
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201 if 'scoring' in options: |
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202 primary_scoring = options['scoring']['primary_scoring'] |
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203 options['scoring'] = get_scoring(options['scoring']) |
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204 if 'pre_dispatch' in options and options['pre_dispatch'] == '': |
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205 options['pre_dispatch'] = None |
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206 |
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207 ## Set up validator, run estimator through validator and return results. |
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208 |
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209 validator = params['model_validation_functions']['selected_function'] |
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210 validator = getattr(_validation, validator) |
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211 |
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212 selected_function = params['model_validation_functions']['selected_function'] |
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213 |
2
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214 if selected_function == 'cross_validate': |
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215 res = validator(estimator, X, y, **options) |
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216 stat = {} |
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217 for k, v in res.items(): |
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218 if k.startswith('test'): |
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219 stat['mean_' + k] = np.mean(v) |
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220 stat['std_' + k] = np.std(v) |
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221 res.update(stat) |
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222 rval = pd.DataFrame(res) |
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223 rval = rval[sorted(rval.columns)] |
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224 elif selected_function == 'cross_val_predict': |
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225 predicted = validator(estimator, X, y, **options) |
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226 if len(predicted.shape) == 1: |
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227 rval = pd.DataFrame(predicted, columns=['Predicted']) |
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228 else: |
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229 rval = pd.DataFrame(predicted) |
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230 elif selected_function == 'learning_curve': |
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231 try: |
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232 train_sizes = safe_eval(options['train_sizes']) |
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233 except: |
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234 sys.exit("Unsupported train_sizes input! Supports int/float in tuple and array-like structure.") |
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235 if type(train_sizes) is tuple: |
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236 train_sizes = np.linspace(*train_sizes) |
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237 options['train_sizes'] = train_sizes |
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238 train_sizes_abs, train_scores, test_scores = validator(estimator, X, y, **options) |
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239 rval = pd.DataFrame(dict( |
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240 train_sizes_abs = train_sizes_abs, |
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241 mean_train_scores = np.mean(train_scores, axis=1), |
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242 std_train_scores = np.std(train_scores, axis=1), |
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243 mean_test_scores = np.mean(test_scores, axis=1), |
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244 std_test_scores = np.std(test_scores, axis=1))) |
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245 rval = rval[['train_sizes_abs', 'mean_train_scores', 'std_train_scores', |
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246 'mean_test_scores', 'std_test_scores']] |
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247 elif selected_function == 'permutation_test_score': |
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248 score, permutation_scores, pvalue = validator(estimator, X, y, **options) |
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249 permutation_scores_df = pd.DataFrame(dict( |
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250 permutation_scores = permutation_scores)) |
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251 score_df = pd.DataFrame(dict( |
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252 score = [score], |
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253 pvalue = [pvalue])) |
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254 rval = pd.concat([score_df[['score', 'pvalue']], permutation_scores_df], axis=1) |
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255 |
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256 rval.to_csv(path_or_buf='$outfile', sep='\t', header=True, index=False) |
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257 |
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258 ]]> |
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259 </configfile> |
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260 </configfiles> |
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261 <inputs> |
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262 <param name="infile_estimator" type="data" format="h5mlm" label="Choose the dataset containing model/pipeline object" /> |
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263 <conditional name="model_validation_functions"> |
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264 <param name="selected_function" type="select" label="Select a model validation function"> |
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265 <option value="cross_validate">cross_validate - Evaluate metric(s) by cross-validation and also record fit/score times</option> |
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266 <option value="cross_val_predict">cross_val_predict - Generate cross-validated estimates for each input data point</option> |
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267 <option value="learning_curve">learning_curve - Learning curve</option> |
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268 <option value="permutation_test_score">permutation_test_score - Evaluate the significance of a cross-validated score with permutations</option> |
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269 <option value="validation_curve">validation_curve - Use grid search with one parameter instead</option> |
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270 </param> |
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271 <when value="cross_validate"> |
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272 <section name="options" title="Other Options" expanded="false"> |
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273 <expand macro="scoring_selection" /> |
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274 <expand macro="model_validation_common_options" /> |
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275 <param argument="return_train_score" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" help="Whether to include train scores." /> |
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276 <!--param argument="return_estimator" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" help="Whether to return the estimators fitted on each split." /> --> |
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277 <!--param argument="error_score" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Raise fit error:" help="If false, the metric score is assigned to NaN if an error occurs in estimator fitting and FitFailedWarning is raised." /> --> |
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278 <!--fit_params--> |
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279 <expand macro="pre_dispatch" /> |
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280 </section> |
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281 </when> |
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282 <when value="cross_val_predict"> |
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283 <section name="options" title="Other Options" expanded="false"> |
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284 <expand macro="model_validation_common_options" /> |
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285 <!--fit_params--> |
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286 <expand macro="pre_dispatch" value="2*n_jobs’" help="Controls the number of jobs that get dispatched during parallel execution" /> |
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287 <param argument="method" type="select" label="Invokes the passed method name of the passed estimator"> |
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288 <option value="predict" selected="true">predict</option> |
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289 <option value="predict_proba">predict_proba</option> |
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290 </param> |
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291 </section> |
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292 </when> |
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293 <when value="learning_curve"> |
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294 <section name="options" title="Other Options" expanded="false"> |
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295 <expand macro="scoring_selection" /> |
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296 <expand macro="model_validation_common_options" /> |
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297 <param argument="train_sizes" type="text" value="(0.1, 1.0, 5)" label="train_sizes" |
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298 help="Relative or absolute numbers of training examples that will be used to generate the learning curve. Supports 1) tuple, to be evaled by np.linspace, e.g. (0.1, 1.0, 5); 2) array-like, e.g. [0.1 , 0.325, 0.55 , 0.775, 1.]"> |
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299 <sanitizer> |
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300 <valid initial="default"> |
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301 <add value="[" /> |
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302 <add value="]" /> |
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303 </valid> |
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304 </sanitizer> |
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305 </param> |
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306 <param argument="exploit_incremental_learning" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" help="Whether to apply incremental learning to speed up fitting of the estimator if supported" /> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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307 <expand macro="pre_dispatch" /> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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308 <expand macro="shuffle" checked="false" label="shuffle" help="Whether to shuffle training data before taking prefixes" /> |
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309 <expand macro="random_state" help_text="If int, the seed used by the random number generator. Used when `shuffle` is True" /> |
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310 </section> |
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311 </when> |
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312 <when value="permutation_test_score"> |
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313 <section name="options" title="Other Options" expanded="false"> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
314 <expand macro="scoring_selection" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
315 <expand macro="model_validation_common_options" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
316 <param name="n_permutations" type="integer" value="100" optional="true" label="n_permutations" help="Number of times to permute y" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
317 <expand macro="random_state" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
318 </section> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
319 </when> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
320 <when value="validation_curve" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
321 </conditional> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
322 <expand macro="sl_mixed_input_plus_sequence" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
323 </inputs> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
324 <outputs> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
325 <data format="tabular" name="outfile" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
326 </outputs> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
327 <tests> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
328 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
329 <param name="infile_estimator" value="pipeline02" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
330 <param name="selected_function" value="cross_validate" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
331 <param name="return_train_score" value="True" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
332 <param name="infile1" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
333 <param name="col1" value="1,2,3,4,5" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
334 <param name="infile2" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
335 <param name="col2" value="6" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
336 <output name="outfile"> |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
337 <assert_contents> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
338 <has_n_columns n="6" /> |
34
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
339 <has_text text="0.9998136508657879" /> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
340 <has_text text="0.9999980090366614" /> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
341 <has_text text="0.9999977541353663" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
342 </assert_contents> |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
343 </output> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
344 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
345 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
346 <param name="infile_estimator" value="pipeline02" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
347 <param name="selected_function" value="cross_val_predict" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
348 <param name="infile1" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
349 <param name="col1" value="1,2,3,4,5" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
350 <param name="infile2" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
351 <param name="col2" value="6" /> |
34
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
352 <output name="outfile"> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
353 <assert_contents> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
354 <has_n_columns n="1" /> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
355 <has_text text="1.5781414" /> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
356 <has_text text="-1.19994559787" /> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
357 <has_text text="-0.7187446" /> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
358 <has_text text="0.324693926" /> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
359 <has_text text="1.25823227" /> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
360 </assert_contents> |
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
361 </output> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
362 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
363 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
364 <param name="infile_estimator" value="pipeline05" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
365 <param name="selected_function" value="learning_curve" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
366 <param name="infile1" value="regression_X.tabular" ftype="tabular" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
367 <param name="header1" value="true" /> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
368 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
369 <param name="infile2" value="regression_y.tabular" ftype="tabular" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
370 <param name="header2" value="true" /> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
371 <param name="col2" value="1" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
372 <output name="outfile" file="mv_result03.tabular" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
373 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
374 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
375 <param name="infile_estimator" value="pipeline05" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
376 <param name="selected_function" value="permutation_test_score" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
377 <param name="infile1" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
378 <param name="col1" value="1,2,3,4,5" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
379 <param name="infile2" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
380 <param name="col2" value="6" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
381 <output name="outfile"> |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
382 <assert_contents> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
383 <has_n_columns n="3" /> |
34
1fe00785190d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
384 <has_text text="-2.7453395018288753" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
385 </assert_contents> |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
386 </output> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
387 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
388 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
389 <param name="infile_estimator" value="pipeline05" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
390 <param name="selected_function" value="cross_val_predict" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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391 <section name="groups_selector"> |
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9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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392 <param name="infile_groups" value="regression_y.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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393 <param name="header_g" value="true" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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394 <param name="selected_column_selector_option_g" value="by_index_number" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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395 <param name="col_g" value="1" /> |
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cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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396 </section> |
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9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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397 <param name="selected_cv" value="GroupKFold" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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398 <param name="infile1" value="regression_X.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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399 <param name="header1" value="true" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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400 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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401 <param name="infile2" value="regression_y.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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402 <param name="header2" value="true" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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403 <param name="col2" value="1" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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404 <output name="outfile" file="mv_result05.tabular" /> |
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333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
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405 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
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406 </tests> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
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407 <help> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
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408 <![CDATA[ |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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409 **What it does** |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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410 This tool includes model validation functions to evaluate estimator performance in the cross-validation approach. This tool is based on |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
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411 sklearn.model_selection package. |
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c6b3efcba7bd
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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412 For information about model validation functions and their parameter settings please refer to `Scikit-learn model_selection`_. |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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413 |
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c6b3efcba7bd
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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414 .. _`Scikit-learn model_selection`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.model_selection |
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333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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415 ]]> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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416 </help> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cf3d813ec755166ee0bd517b4ecbbd4f84d4df1
bgruening
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417 <expand macro="sklearn_citation"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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418 <expand macro="skrebate_citation" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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419 <expand macro="xgboost_citation" /> |
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badd86b9ce24
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cf3d813ec755166ee0bd517b4ecbbd4f84d4df1
bgruening
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420 </expand> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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421 </tool> |