Mercurial > repos > bgruening > sklearn_regression_metrics
annotate search_model_validation.py @ 20:203b2ade8097 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
author | bgruening |
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date | Fri, 13 Sep 2019 12:13:26 -0400 |
parents | 28d51b976c29 |
children | a152c1d23379 |
rev | line source |
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40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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1 import argparse |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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2 import collections |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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3 import imblearn |
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28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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4 import joblib |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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5 import json |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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6 import numpy as np |
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28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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7 import pandas as pd |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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8 import pickle |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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9 import skrebate |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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10 import sklearn |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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11 import sys |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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12 import xgboost |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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13 import warnings |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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14 from imblearn import under_sampling, over_sampling, combine |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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15 from scipy.io import mmread |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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16 from mlxtend import classifier, regressor |
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28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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17 from sklearn.base import clone |
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40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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18 from sklearn import (cluster, compose, decomposition, ensemble, |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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19 feature_extraction, feature_selection, |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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20 gaussian_process, kernel_approximation, metrics, |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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21 model_selection, naive_bayes, neighbors, |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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22 pipeline, preprocessing, svm, linear_model, |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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23 tree, discriminant_analysis) |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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24 from sklearn.exceptions import FitFailedWarning |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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25 from sklearn.model_selection._validation import _score, cross_validate |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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26 from sklearn.model_selection import _search, _validation |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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27 |
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28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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28 from galaxy_ml.utils import (SafeEval, get_cv, get_scoring, load_model, |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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29 read_columns, try_get_attr, get_module) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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30 |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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31 |
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28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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32 _fit_and_score = try_get_attr('galaxy_ml.model_validations', '_fit_and_score') |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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33 setattr(_search, '_fit_and_score', _fit_and_score) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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34 setattr(_validation, '_fit_and_score', _fit_and_score) |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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35 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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36 N_JOBS = int(__import__('os').environ.get('GALAXY_SLOTS', 1)) |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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37 CACHE_DIR = './cached' |
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28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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38 NON_SEARCHABLE = ('n_jobs', 'pre_dispatch', 'memory', '_path', |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 'nthread', 'callbacks') |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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40 ALLOWED_CALLBACKS = ('EarlyStopping', 'TerminateOnNaN', 'ReduceLROnPlateau', |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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41 'CSVLogger', 'None') |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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42 |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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43 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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44 def _eval_search_params(params_builder): |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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45 search_params = {} |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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46 |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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47 for p in params_builder['param_set']: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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48 search_list = p['sp_list'].strip() |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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49 if search_list == '': |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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50 continue |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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51 |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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52 param_name = p['sp_name'] |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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53 if param_name.lower().endswith(NON_SEARCHABLE): |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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54 print("Warning: `%s` is not eligible for search and was " |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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55 "omitted!" % param_name) |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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56 continue |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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57 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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58 if not search_list.startswith(':'): |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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59 safe_eval = SafeEval(load_scipy=True, load_numpy=True) |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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60 ev = safe_eval(search_list) |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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61 search_params[param_name] = ev |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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62 else: |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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63 # Have `:` before search list, asks for estimator evaluatio |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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64 safe_eval_es = SafeEval(load_estimators=True) |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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65 search_list = search_list[1:].strip() |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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66 # TODO maybe add regular express check |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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67 ev = safe_eval_es(search_list) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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68 preprocessings = ( |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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69 preprocessing.StandardScaler(), preprocessing.Binarizer(), |
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28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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70 preprocessing.MaxAbsScaler(), |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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71 preprocessing.Normalizer(), preprocessing.MinMaxScaler(), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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72 preprocessing.PolynomialFeatures(), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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73 preprocessing.RobustScaler(), feature_selection.SelectKBest(), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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74 feature_selection.GenericUnivariateSelect(), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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75 feature_selection.SelectPercentile(), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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76 feature_selection.SelectFpr(), feature_selection.SelectFdr(), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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77 feature_selection.SelectFwe(), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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78 feature_selection.VarianceThreshold(), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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79 decomposition.FactorAnalysis(random_state=0), |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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80 decomposition.FastICA(random_state=0), |
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81 decomposition.IncrementalPCA(), |
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82 decomposition.KernelPCA(random_state=0, n_jobs=N_JOBS), |
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83 decomposition.LatentDirichletAllocation( |
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84 random_state=0, n_jobs=N_JOBS), |
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85 decomposition.MiniBatchDictionaryLearning( |
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86 random_state=0, n_jobs=N_JOBS), |
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87 decomposition.MiniBatchSparsePCA( |
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88 random_state=0, n_jobs=N_JOBS), |
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89 decomposition.NMF(random_state=0), |
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90 decomposition.PCA(random_state=0), |
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91 decomposition.SparsePCA(random_state=0, n_jobs=N_JOBS), |
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92 decomposition.TruncatedSVD(random_state=0), |
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93 kernel_approximation.Nystroem(random_state=0), |
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94 kernel_approximation.RBFSampler(random_state=0), |
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95 kernel_approximation.AdditiveChi2Sampler(), |
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96 kernel_approximation.SkewedChi2Sampler(random_state=0), |
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97 cluster.FeatureAgglomeration(), |
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98 skrebate.ReliefF(n_jobs=N_JOBS), |
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99 skrebate.SURF(n_jobs=N_JOBS), |
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100 skrebate.SURFstar(n_jobs=N_JOBS), |
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101 skrebate.MultiSURF(n_jobs=N_JOBS), |
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102 skrebate.MultiSURFstar(n_jobs=N_JOBS), |
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103 imblearn.under_sampling.ClusterCentroids( |
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104 random_state=0, n_jobs=N_JOBS), |
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105 imblearn.under_sampling.CondensedNearestNeighbour( |
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106 random_state=0, n_jobs=N_JOBS), |
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107 imblearn.under_sampling.EditedNearestNeighbours( |
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108 random_state=0, n_jobs=N_JOBS), |
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109 imblearn.under_sampling.RepeatedEditedNearestNeighbours( |
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110 random_state=0, n_jobs=N_JOBS), |
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111 imblearn.under_sampling.AllKNN(random_state=0, n_jobs=N_JOBS), |
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112 imblearn.under_sampling.InstanceHardnessThreshold( |
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113 random_state=0, n_jobs=N_JOBS), |
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114 imblearn.under_sampling.NearMiss( |
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115 random_state=0, n_jobs=N_JOBS), |
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116 imblearn.under_sampling.NeighbourhoodCleaningRule( |
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117 random_state=0, n_jobs=N_JOBS), |
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118 imblearn.under_sampling.OneSidedSelection( |
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119 random_state=0, n_jobs=N_JOBS), |
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120 imblearn.under_sampling.RandomUnderSampler( |
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121 random_state=0), |
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122 imblearn.under_sampling.TomekLinks( |
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123 random_state=0, n_jobs=N_JOBS), |
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124 imblearn.over_sampling.ADASYN(random_state=0, n_jobs=N_JOBS), |
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125 imblearn.over_sampling.RandomOverSampler(random_state=0), |
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126 imblearn.over_sampling.SMOTE(random_state=0, n_jobs=N_JOBS), |
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127 imblearn.over_sampling.SVMSMOTE(random_state=0, n_jobs=N_JOBS), |
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128 imblearn.over_sampling.BorderlineSMOTE( |
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129 random_state=0, n_jobs=N_JOBS), |
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130 imblearn.over_sampling.SMOTENC( |
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131 categorical_features=[], random_state=0, n_jobs=N_JOBS), |
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132 imblearn.combine.SMOTEENN(random_state=0), |
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133 imblearn.combine.SMOTETomek(random_state=0)) |
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134 newlist = [] |
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135 for obj in ev: |
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136 if obj is None: |
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137 newlist.append(None) |
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138 elif obj == 'all_0': |
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139 newlist.extend(preprocessings[0:35]) |
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140 elif obj == 'sk_prep_all': # no KernalCenter() |
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141 newlist.extend(preprocessings[0:7]) |
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142 elif obj == 'fs_all': |
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143 newlist.extend(preprocessings[7:14]) |
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144 elif obj == 'decomp_all': |
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145 newlist.extend(preprocessings[14:25]) |
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146 elif obj == 'k_appr_all': |
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147 newlist.extend(preprocessings[25:29]) |
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148 elif obj == 'reb_all': |
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149 newlist.extend(preprocessings[30:35]) |
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150 elif obj == 'imb_all': |
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151 newlist.extend(preprocessings[35:54]) |
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152 elif type(obj) is int and -1 < obj < len(preprocessings): |
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153 newlist.append(preprocessings[obj]) |
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154 elif hasattr(obj, 'get_params'): # user uploaded object |
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155 if 'n_jobs' in obj.get_params(): |
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156 newlist.append(obj.set_params(n_jobs=N_JOBS)) |
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157 else: |
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158 newlist.append(obj) |
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159 else: |
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160 sys.exit("Unsupported estimator type: %r" % (obj)) |
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161 |
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162 search_params[param_name] = newlist |
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163 |
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164 return search_params |
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165 |
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166 |
17
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167 def main(inputs, infile_estimator, infile1, infile2, |
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168 outfile_result, outfile_object=None, |
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169 outfile_weights=None, groups=None, |
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170 ref_seq=None, intervals=None, targets=None, |
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171 fasta_path=None): |
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172 """ |
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173 Parameter |
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174 --------- |
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175 inputs : str |
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176 File path to galaxy tool parameter |
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177 |
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178 infile_estimator : str |
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179 File path to estimator |
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180 |
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181 infile1 : str |
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182 File path to dataset containing features |
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183 |
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184 infile2 : str |
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185 File path to dataset containing target values |
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186 |
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187 outfile_result : str |
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188 File path to save the results, either cv_results or test result |
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189 |
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190 outfile_object : str, optional |
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191 File path to save searchCV object |
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192 |
19
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193 outfile_weights : str, optional |
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194 File path to save model weights |
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195 |
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196 groups : str |
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197 File path to dataset containing groups labels |
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198 |
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199 ref_seq : str |
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200 File path to dataset containing genome sequence file |
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201 |
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202 intervals : str |
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203 File path to dataset containing interval file |
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204 |
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205 targets : str |
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206 File path to dataset compressed target bed file |
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207 |
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208 fasta_path : str |
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209 File path to dataset containing fasta file |
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210 """ |
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211 warnings.simplefilter('ignore') |
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212 |
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213 with open(inputs, 'r') as param_handler: |
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214 params = json.load(param_handler) |
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215 |
20
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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216 # conflict param checker |
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217 if params['outer_split']['split_mode'] == 'nested_cv' \ |
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218 and params['save'] != 'nope': |
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219 raise ValueError("Save best estimator is not possible for nested CV!") |
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220 |
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221 if not (params['search_schemes']['options']['refit']) \ |
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222 and params['save'] != 'nope': |
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223 raise ValueError("Save best estimator is not possible when refit " |
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224 "is False!") |
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225 |
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226 params_builder = params['search_schemes']['search_params_builder'] |
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227 |
19
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228 with open(infile_estimator, 'rb') as estimator_handler: |
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229 estimator = load_model(estimator_handler) |
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230 estimator_params = estimator.get_params() |
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231 |
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232 # store read dataframe object |
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233 loaded_df = {} |
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234 |
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235 input_type = params['input_options']['selected_input'] |
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236 # tabular input |
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237 if input_type == 'tabular': |
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238 header = 'infer' if params['input_options']['header1'] else None |
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239 column_option = (params['input_options']['column_selector_options_1'] |
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240 ['selected_column_selector_option']) |
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241 if column_option in ['by_index_number', 'all_but_by_index_number', |
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242 'by_header_name', 'all_but_by_header_name']: |
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243 c = params['input_options']['column_selector_options_1']['col1'] |
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244 else: |
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245 c = None |
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246 |
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247 df_key = infile1 + repr(header) |
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248 df = pd.read_csv(infile1, sep='\t', header=header, |
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249 parse_dates=True) |
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250 loaded_df[df_key] = df |
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251 |
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252 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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253 # sparse input |
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254 elif input_type == 'sparse': |
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255 X = mmread(open(infile1, 'r')) |
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256 |
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257 # fasta_file input |
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258 elif input_type == 'seq_fasta': |
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259 pyfaidx = get_module('pyfaidx') |
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260 sequences = pyfaidx.Fasta(fasta_path) |
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261 n_seqs = len(sequences.keys()) |
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262 X = np.arange(n_seqs)[:, np.newaxis] |
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263 for param in estimator_params.keys(): |
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264 if param.endswith('fasta_path'): |
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265 estimator.set_params( |
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266 **{param: fasta_path}) |
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267 break |
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268 else: |
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269 raise ValueError( |
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270 "The selected estimator doesn't support " |
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271 "fasta file input! Please consider using " |
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272 "KerasGBatchClassifier with " |
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273 "FastaDNABatchGenerator/FastaProteinBatchGenerator " |
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274 "or having GenomeOneHotEncoder/ProteinOneHotEncoder " |
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275 "in pipeline!") |
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276 |
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277 elif input_type == 'refseq_and_interval': |
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278 path_params = { |
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279 'data_batch_generator__ref_genome_path': ref_seq, |
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280 'data_batch_generator__intervals_path': intervals, |
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281 'data_batch_generator__target_path': targets |
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282 } |
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283 estimator.set_params(**path_params) |
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284 n_intervals = sum(1 for line in open(intervals)) |
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285 X = np.arange(n_intervals)[:, np.newaxis] |
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286 |
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287 # Get target y |
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288 header = 'infer' if params['input_options']['header2'] else None |
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289 column_option = (params['input_options']['column_selector_options_2'] |
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290 ['selected_column_selector_option2']) |
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291 if column_option in ['by_index_number', 'all_but_by_index_number', |
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292 'by_header_name', 'all_but_by_header_name']: |
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293 c = params['input_options']['column_selector_options_2']['col2'] |
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294 else: |
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295 c = None |
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296 |
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297 df_key = infile2 + repr(header) |
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298 if df_key in loaded_df: |
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299 infile2 = loaded_df[df_key] |
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300 else: |
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301 infile2 = pd.read_csv(infile2, sep='\t', |
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302 header=header, parse_dates=True) |
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303 loaded_df[df_key] = infile2 |
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304 |
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305 y = read_columns( |
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306 infile2, |
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307 c=c, |
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308 c_option=column_option, |
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309 sep='\t', |
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310 header=header, |
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311 parse_dates=True) |
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312 if len(y.shape) == 2 and y.shape[1] == 1: |
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313 y = y.ravel() |
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314 if input_type == 'refseq_and_interval': |
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315 estimator.set_params( |
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316 data_batch_generator__features=y.ravel().tolist()) |
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317 y = None |
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318 # end y |
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319 |
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320 optimizer = params['search_schemes']['selected_search_scheme'] |
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321 optimizer = getattr(model_selection, optimizer) |
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322 |
19
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323 # handle gridsearchcv options |
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324 options = params['search_schemes']['options'] |
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325 |
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326 if groups: |
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327 header = 'infer' if (options['cv_selector']['groups_selector'] |
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328 ['header_g']) else None |
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329 column_option = (options['cv_selector']['groups_selector'] |
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330 ['column_selector_options_g'] |
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331 ['selected_column_selector_option_g']) |
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332 if column_option in ['by_index_number', 'all_but_by_index_number', |
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333 'by_header_name', 'all_but_by_header_name']: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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334 c = (options['cv_selector']['groups_selector'] |
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335 ['column_selector_options_g']['col_g']) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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336 else: |
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337 c = None |
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338 |
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339 df_key = groups + repr(header) |
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340 if df_key in loaded_df: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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341 groups = loaded_df[df_key] |
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342 |
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343 groups = read_columns( |
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344 groups, |
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345 c=c, |
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346 c_option=column_option, |
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347 sep='\t', |
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348 header=header, |
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349 parse_dates=True) |
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350 groups = groups.ravel() |
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351 options['cv_selector']['groups_selector'] = groups |
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352 |
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353 splitter, groups = get_cv(options.pop('cv_selector')) |
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354 options['cv'] = splitter |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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355 options['n_jobs'] = N_JOBS |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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356 primary_scoring = options['scoring']['primary_scoring'] |
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357 options['scoring'] = get_scoring(options['scoring']) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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358 if options['error_score']: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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359 options['error_score'] = 'raise' |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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360 else: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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361 options['error_score'] = np.NaN |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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362 if options['refit'] and isinstance(options['scoring'], dict): |
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363 options['refit'] = primary_scoring |
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364 if 'pre_dispatch' in options and options['pre_dispatch'] == '': |
268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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365 options['pre_dispatch'] = None |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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366 |
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367 # del loaded_df |
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368 del loaded_df |
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369 |
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370 # handle memory |
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371 memory = joblib.Memory(location=CACHE_DIR, verbose=0) |
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372 # cache iraps_core fits could increase search speed significantly |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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373 if estimator.__class__.__name__ == 'IRAPSClassifier': |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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374 estimator.set_params(memory=memory) |
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375 else: |
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376 # For iraps buried in pipeline |
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377 for p, v in estimator_params.items(): |
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378 if p.endswith('memory'): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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379 # for case of `__irapsclassifier__memory` |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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380 if len(p) > 8 and p[:-8].endswith('irapsclassifier'): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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381 # cache iraps_core fits could increase search |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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382 # speed significantly |
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383 new_params = {p: memory} |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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384 estimator.set_params(**new_params) |
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385 # security reason, we don't want memory being |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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386 # modified unexpectedly |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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387 elif v: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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388 new_params = {p, None} |
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389 estimator.set_params(**new_params) |
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390 # For now, 1 CPU is suggested for iprasclassifier |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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391 elif p.endswith('n_jobs'): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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392 new_params = {p: 1} |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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393 estimator.set_params(**new_params) |
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394 # for security reason, types of callbacks are limited |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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395 elif p.endswith('callbacks'): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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396 for cb in v: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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397 cb_type = cb['callback_selection']['callback_type'] |
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398 if cb_type not in ALLOWED_CALLBACKS: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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399 raise ValueError( |
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400 "Prohibited callback type: %s!" % cb_type) |
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401 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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402 param_grid = _eval_search_params(params_builder) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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changeset
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403 searcher = optimizer(estimator, param_grid, **options) |
16
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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parents:
diff
changeset
|
404 |
19
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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405 # do nested split |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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406 split_mode = params['outer_split'].pop('split_mode') |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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407 # nested CV, outer cv using cross_validate |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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408 if split_mode == 'nested_cv': |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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409 outer_cv, _ = get_cv(params['outer_split']['cv_selector']) |
17
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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changeset
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410 |
19
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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411 if options['error_score'] == 'raise': |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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412 rval = cross_validate( |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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413 searcher, X, y, scoring=options['scoring'], |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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414 cv=outer_cv, n_jobs=N_JOBS, verbose=0, |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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415 error_score=options['error_score']) |
17
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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416 else: |
19
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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417 warnings.simplefilter('always', FitFailedWarning) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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418 with warnings.catch_warnings(record=True) as w: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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419 try: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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420 rval = cross_validate( |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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421 searcher, X, y, |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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422 scoring=options['scoring'], |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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423 cv=outer_cv, n_jobs=N_JOBS, |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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424 verbose=0, |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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425 error_score=options['error_score']) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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426 except ValueError: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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427 pass |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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428 for warning in w: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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429 print(repr(warning.message)) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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430 |
19
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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431 keys = list(rval.keys()) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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432 for k in keys: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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433 if k.startswith('test'): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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434 rval['mean_' + k] = np.mean(rval[k]) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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435 rval['std_' + k] = np.std(rval[k]) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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436 if k.endswith('time'): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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437 rval.pop(k) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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438 rval = pd.DataFrame(rval) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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439 rval = rval[sorted(rval.columns)] |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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440 rval.to_csv(path_or_buf=outfile_result, sep='\t', |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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441 header=True, index=False) |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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442 else: |
19
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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443 if split_mode == 'train_test_split': |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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444 train_test_split = try_get_attr( |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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445 'galaxy_ml.model_validations', 'train_test_split') |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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446 # make sure refit is choosen |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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447 # this could be True for sklearn models, but not the case for |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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448 # deep learning models |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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449 if not options['refit'] and \ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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450 not all(hasattr(estimator, attr) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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451 for attr in ('config', 'model_type')): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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452 warnings.warn("Refit is change to `True` for nested " |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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453 "validation!") |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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454 setattr(searcher, 'refit', True) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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455 split_options = params['outer_split'] |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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changeset
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456 |
19
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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457 # splits |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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458 if split_options['shuffle'] == 'stratified': |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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459 split_options['labels'] = y |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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460 X, X_test, y, y_test = train_test_split(X, y, **split_options) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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461 elif split_options['shuffle'] == 'group': |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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462 if groups is None: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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463 raise ValueError("No group based CV option was " |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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464 "choosen for group shuffle!") |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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465 split_options['labels'] = groups |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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466 if y is None: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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467 X, X_test, groups, _ =\ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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468 train_test_split(X, groups, **split_options) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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469 else: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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470 X, X_test, y, y_test, groups, _ =\ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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471 train_test_split(X, y, groups, **split_options) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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472 else: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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473 if split_options['shuffle'] == 'None': |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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474 split_options['shuffle'] = None |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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475 X, X_test, y, y_test =\ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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476 train_test_split(X, y, **split_options) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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477 # end train_test_split |
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changeset
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478 |
19
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479 # shared by both train_test_split and non-split |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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480 if options['error_score'] == 'raise': |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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481 searcher.fit(X, y, groups=groups) |
17
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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diff
changeset
|
482 else: |
19
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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483 warnings.simplefilter('always', FitFailedWarning) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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484 with warnings.catch_warnings(record=True) as w: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
485 try: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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486 searcher.fit(X, y, groups=groups) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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487 except ValueError: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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parents:
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changeset
|
488 pass |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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489 for warning in w: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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490 print(repr(warning.message)) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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491 |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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492 # no outer split |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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493 if split_mode == 'no': |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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494 # save results |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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495 cv_results = pd.DataFrame(searcher.cv_results_) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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496 cv_results = cv_results[sorted(cv_results.columns)] |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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497 cv_results.to_csv(path_or_buf=outfile_result, sep='\t', |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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498 header=True, index=False) |
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268ecaf96b68
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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changeset
|
499 |
19
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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500 # train_test_split, output test result using best_estimator_ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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501 # or rebuild the trained estimator using weights if applicable. |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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502 else: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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503 scorer_ = searcher.scorer_ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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504 if isinstance(scorer_, collections.Mapping): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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505 is_multimetric = True |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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506 else: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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507 is_multimetric = False |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
508 |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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509 best_estimator_ = getattr(searcher, 'best_estimator_', None) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
510 if not best_estimator_: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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511 raise ValueError("GridSearchCV object has no " |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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512 "`best_estimator_` when `refit`=False!") |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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513 |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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514 if best_estimator_.__class__.__name__ == 'KerasGBatchClassifier' \ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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parents:
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515 and hasattr(estimator.data_batch_generator, 'target_path'): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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516 test_score = best_estimator_.evaluate( |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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517 X_test, scorer=scorer_, is_multimetric=is_multimetric) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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518 else: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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519 test_score = _score(best_estimator_, X_test, |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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520 y_test, scorer_, |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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521 is_multimetric=is_multimetric) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
522 |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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523 if not is_multimetric: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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524 test_score = {primary_scoring: test_score} |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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525 for key, value in test_score.items(): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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526 test_score[key] = [value] |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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527 result_df = pd.DataFrame(test_score) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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528 result_df.to_csv(path_or_buf=outfile_result, sep='\t', |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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529 header=True, index=False) |
17
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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changeset
|
530 |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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changeset
|
531 memory.clear(warn=False) |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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changeset
|
532 |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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changeset
|
533 if outfile_object: |
19
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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534 best_estimator_ = getattr(searcher, 'best_estimator_', None) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
535 if not best_estimator_: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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536 warnings.warn("GridSearchCV object has no attribute " |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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537 "'best_estimator_', because either it's " |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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538 "nested gridsearch or `refit` is False!") |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
539 return |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
540 |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
541 main_est = best_estimator_ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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542 if isinstance(best_estimator_, pipeline.Pipeline): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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543 main_est = best_estimator_.steps[-1][-1] |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
544 |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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545 if hasattr(main_est, 'model_') \ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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546 and hasattr(main_est, 'save_weights'): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
547 if outfile_weights: |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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548 main_est.save_weights(outfile_weights) |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
549 del main_est.model_ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
550 del main_est.fit_params |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
551 del main_est.model_class_ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
552 del main_est.validation_data |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
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553 if getattr(main_est, 'data_generator_', None): |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
554 del main_est.data_generator_ |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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changeset
|
555 |
17
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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changeset
|
556 with open(outfile_object, 'wb') as output_handler: |
19
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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557 pickle.dump(best_estimator_, output_handler, |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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558 pickle.HIGHEST_PROTOCOL) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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559 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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560 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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561 if __name__ == '__main__': |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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562 aparser = argparse.ArgumentParser() |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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563 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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564 aparser.add_argument("-e", "--estimator", dest="infile_estimator") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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565 aparser.add_argument("-X", "--infile1", dest="infile1") |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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566 aparser.add_argument("-y", "--infile2", dest="infile2") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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567 aparser.add_argument("-O", "--outfile_result", dest="outfile_result") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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568 aparser.add_argument("-o", "--outfile_object", dest="outfile_object") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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569 aparser.add_argument("-w", "--outfile_weights", dest="outfile_weights") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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570 aparser.add_argument("-g", "--groups", dest="groups") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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571 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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572 aparser.add_argument("-b", "--intervals", dest="intervals") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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573 aparser.add_argument("-t", "--targets", dest="targets") |
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574 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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575 args = aparser.parse_args() |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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576 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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577 main(args.inputs, args.infile_estimator, args.infile1, args.infile2, |
40ee30b5e456
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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578 args.outfile_result, outfile_object=args.outfile_object, |
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579 outfile_weights=args.outfile_weights, groups=args.groups, |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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580 ref_seq=args.ref_seq, intervals=args.intervals, |
28d51b976c29
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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581 targets=args.targets, fasta_path=args.fasta_path) |