Mercurial > repos > bgruening > sklearn_regression_metrics
annotate keras_train_and_eval.py @ 34:642452aeed0d draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
author | bgruening |
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date | Wed, 09 Aug 2023 13:51:11 +0000 |
parents | 70c5a9127f99 |
children | dc17e2878dc1 |
rev | line source |
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a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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1 import argparse |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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2 import json |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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3 import os |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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4 import warnings |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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5 from itertools import chain |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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6 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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7 import joblib |
9c8ede554b7c
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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8 import numpy as np |
9c8ede554b7c
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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9 import pandas as pd |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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10 from galaxy_ml.keras_galaxy_models import ( |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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11 _predict_generator, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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12 KerasGBatchClassifier, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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13 ) |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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14 from galaxy_ml.model_persist import dump_model_to_h5, load_model_from_h5 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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15 from galaxy_ml.model_validations import train_test_split |
34
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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16 from galaxy_ml.utils import ( |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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17 clean_params, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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18 gen_compute_scores, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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19 get_main_estimator, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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20 get_module, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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21 get_scoring, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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22 read_columns, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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23 SafeEval |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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24 ) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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25 from scipy.io import mmread |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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26 from sklearn.metrics._scorer import _check_multimetric_scoring |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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27 from sklearn.model_selection._validation import _score |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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28 from sklearn.utils import _safe_indexing, indexable |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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29 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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30 N_JOBS = int(os.environ.get("GALAXY_SLOTS", 1)) |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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31 CACHE_DIR = os.path.join(os.getcwd(), "cached") |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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32 NON_SEARCHABLE = ( |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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33 "n_jobs", |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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34 "pre_dispatch", |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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35 "memory", |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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36 "_path", |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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37 "_dir", |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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38 "nthread", |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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39 "callbacks", |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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40 ) |
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41 ALLOWED_CALLBACKS = ( |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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42 "EarlyStopping", |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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43 "TerminateOnNaN", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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44 "ReduceLROnPlateau", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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45 "CSVLogger", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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46 "None", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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47 ) |
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48 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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49 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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50 def _eval_swap_params(params_builder): |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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51 swap_params = {} |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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52 |
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53 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 e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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54 swap_value = p["sp_value"].strip() |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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55 if swap_value == "": |
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56 continue |
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57 |
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58 param_name = p["sp_name"] |
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59 if param_name.lower().endswith(NON_SEARCHABLE): |
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60 warnings.warn( |
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61 "Warning: `%s` is not eligible for search and was " |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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62 "omitted!" % param_name |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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63 ) |
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64 continue |
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65 |
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66 if not swap_value.startswith(":"): |
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67 safe_eval = SafeEval(load_scipy=True, load_numpy=True) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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68 ev = safe_eval(swap_value) |
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69 else: |
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70 # Have `:` before search list, asks for estimator evaluatio |
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71 safe_eval_es = SafeEval(load_estimators=True) |
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72 swap_value = swap_value[1:].strip() |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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73 # TODO maybe add regular express check |
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74 ev = safe_eval_es(swap_value) |
a152c1d23379
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75 |
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76 swap_params[param_name] = ev |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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77 |
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78 return swap_params |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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79 |
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80 |
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81 def train_test_split_none(*arrays, **kwargs): |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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82 """extend train_test_split to take None arrays |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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83 and support split by group names. |
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84 """ |
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85 nones = [] |
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86 new_arrays = [] |
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87 for idx, arr in enumerate(arrays): |
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88 if arr is None: |
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89 nones.append(idx) |
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90 else: |
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91 new_arrays.append(arr) |
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92 |
28
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93 if kwargs["shuffle"] == "None": |
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94 kwargs["shuffle"] = None |
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95 |
28
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96 group_names = kwargs.pop("group_names", None) |
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97 |
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98 if group_names is not None and group_names.strip(): |
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99 group_names = [name.strip() for name in group_names.split(",")] |
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100 new_arrays = indexable(*new_arrays) |
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101 groups = kwargs["labels"] |
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102 n_samples = new_arrays[0].shape[0] |
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103 index_arr = np.arange(n_samples) |
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104 test = index_arr[np.isin(groups, group_names)] |
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105 train = index_arr[~np.isin(groups, group_names)] |
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106 rval = list( |
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107 chain.from_iterable( |
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108 (_safe_indexing(a, train), _safe_indexing(a, test)) for a in new_arrays |
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109 ) |
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110 ) |
24
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111 else: |
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112 rval = train_test_split(*new_arrays, **kwargs) |
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113 |
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114 for pos in nones: |
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115 rval[pos * 2: 2] = [None, None] |
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116 |
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117 return rval |
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118 |
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119 |
34
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120 def _evaluate_keras_and_sklearn_scores( |
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121 estimator, |
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122 data_generator, |
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123 X, |
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124 y=None, |
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125 sk_scoring=None, |
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126 steps=None, |
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127 batch_size=32, |
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128 return_predictions=False, |
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129 ): |
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130 """output scores for bother keras and sklearn metrics |
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131 |
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132 Parameters |
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133 ----------- |
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134 estimator : object |
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135 Fitted `galaxy_ml.keras_galaxy_models.KerasGBatchClassifier`. |
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136 data_generator : object |
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137 From `galaxy_ml.preprocessors.ImageDataFrameBatchGenerator`. |
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138 X : 2-D array |
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139 Contains indecies of images that need to be evaluated. |
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140 y : None |
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141 Target value. |
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142 sk_scoring : dict |
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143 Galaxy tool input parameters. |
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144 steps : integer or None |
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145 Evaluation/prediction steps before stop. |
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146 batch_size : integer |
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147 Number of samples in a batch |
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148 return_predictions : bool, default is False |
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149 Whether to return predictions and true labels. |
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150 """ |
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151 scores = {} |
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152 |
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153 generator = data_generator.flow(X, y=y, batch_size=batch_size) |
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154 # keras metrics evaluation |
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155 # handle scorer, convert to scorer dict |
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156 generator.reset() |
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157 score_results = estimator.model_.evaluate_generator(generator, steps=steps) |
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158 metrics_names = estimator.model_.metrics_names |
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159 if not isinstance(metrics_names, list): |
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160 scores[metrics_names] = score_results |
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161 else: |
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162 scores = dict(zip(metrics_names, score_results)) |
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163 |
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164 if sk_scoring["primary_scoring"] == "default" and not return_predictions: |
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165 return scores |
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166 |
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167 generator.reset() |
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168 predictions, y_true = _predict_generator(estimator.model_, generator, steps=steps) |
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169 |
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170 # for sklearn metrics |
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171 if sk_scoring["primary_scoring"] != "default": |
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172 scorer = get_scoring(sk_scoring) |
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173 if not isinstance(scorer, (dict, list)): |
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174 scorer = [sk_scoring["primary_scoring"]] |
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175 scorer = _check_multimetric_scoring(estimator, scoring=scorer) |
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176 sk_scores = gen_compute_scores(y_true, predictions, scorer) |
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177 scores.update(sk_scores) |
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178 |
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179 if return_predictions: |
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180 return scores, predictions, y_true |
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181 else: |
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182 return scores, None, None |
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183 |
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184 |
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185 def main( |
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186 inputs, |
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187 infile_estimator, |
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188 infile1, |
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189 infile2, |
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190 outfile_result, |
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191 outfile_object=None, |
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192 outfile_y_true=None, |
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193 outfile_y_preds=None, |
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194 groups=None, |
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195 ref_seq=None, |
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196 intervals=None, |
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197 targets=None, |
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198 fasta_path=None, |
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199 ): |
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200 """ |
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201 Parameter |
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202 --------- |
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203 inputs : str |
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204 File path to galaxy tool parameter. |
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205 |
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206 infile_estimator : str |
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207 File path to estimator. |
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208 |
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209 infile1 : str |
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210 File path to dataset containing features. |
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211 |
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212 infile2 : str |
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213 File path to dataset containing target values. |
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214 |
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215 outfile_result : str |
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216 File path to save the results, either cv_results or test result. |
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217 |
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218 outfile_object : str, optional |
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219 File path to save searchCV object. |
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220 |
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221 outfile_y_true : str, optional |
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222 File path to target values for prediction. |
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223 |
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224 outfile_y_preds : str, optional |
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225 File path to save predictions. |
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226 |
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227 groups : str |
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228 File path to dataset containing groups labels. |
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229 |
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230 ref_seq : str |
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231 File path to dataset containing genome sequence file. |
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232 |
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233 intervals : str |
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234 File path to dataset containing interval file. |
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235 |
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236 targets : str |
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237 File path to dataset compressed target bed file. |
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238 |
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239 fasta_path : str |
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240 File path to dataset containing fasta file. |
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241 """ |
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242 warnings.simplefilter("ignore") |
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243 |
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244 with open(inputs, "r") as param_handler: |
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245 params = json.load(param_handler) |
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246 |
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247 # load estimator |
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248 estimator = load_model_from_h5(infile_estimator) |
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249 |
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250 estimator = clean_params(estimator) |
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251 |
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252 # swap hyperparameter |
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253 swapping = params["experiment_schemes"]["hyperparams_swapping"] |
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254 swap_params = _eval_swap_params(swapping) |
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255 estimator.set_params(**swap_params) |
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256 |
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257 estimator_params = estimator.get_params() |
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258 |
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259 # store read dataframe object |
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260 loaded_df = {} |
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261 |
28
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262 input_type = params["input_options"]["selected_input"] |
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263 # tabular input |
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264 if input_type == "tabular": |
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265 header = "infer" if params["input_options"]["header1"] else None |
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266 column_option = params["input_options"]["column_selector_options_1"][ |
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267 "selected_column_selector_option" |
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268 ] |
28
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269 if column_option in [ |
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270 "by_index_number", |
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271 "all_but_by_index_number", |
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272 "by_header_name", |
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273 "all_but_by_header_name", |
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274 ]: |
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275 c = params["input_options"]["column_selector_options_1"]["col1"] |
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276 else: |
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277 c = None |
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278 |
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279 df_key = infile1 + repr(header) |
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280 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True) |
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281 loaded_df[df_key] = df |
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282 |
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283 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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284 # sparse input |
28
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285 elif input_type == "sparse": |
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286 X = mmread(open(infile1, "r")) |
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287 |
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288 # fasta_file input |
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289 elif input_type == "seq_fasta": |
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290 pyfaidx = get_module("pyfaidx") |
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291 sequences = pyfaidx.Fasta(fasta_path) |
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292 n_seqs = len(sequences.keys()) |
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293 X = np.arange(n_seqs)[:, np.newaxis] |
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294 for param in estimator_params.keys(): |
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295 if param.endswith("fasta_path"): |
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296 estimator.set_params(**{param: fasta_path}) |
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297 break |
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298 else: |
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299 raise ValueError( |
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300 "The selected estimator doesn't support " |
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301 "fasta file input! Please consider using " |
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302 "KerasGBatchClassifier with " |
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303 "FastaDNABatchGenerator/FastaProteinBatchGenerator " |
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304 "or having GenomeOneHotEncoder/ProteinOneHotEncoder " |
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305 "in pipeline!" |
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306 ) |
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307 |
28
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308 elif input_type == "refseq_and_interval": |
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309 path_params = { |
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310 "data_batch_generator__ref_genome_path": ref_seq, |
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311 "data_batch_generator__intervals_path": intervals, |
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312 "data_batch_generator__target_path": targets, |
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313 } |
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314 estimator.set_params(**path_params) |
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315 n_intervals = sum(1 for line in open(intervals)) |
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316 X = np.arange(n_intervals)[:, np.newaxis] |
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317 |
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318 # Get target y |
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319 header = "infer" if params["input_options"]["header2"] else None |
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320 column_option = params["input_options"]["column_selector_options_2"][ |
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321 "selected_column_selector_option2" |
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322 ] |
28
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323 if column_option in [ |
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324 "by_index_number", |
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325 "all_but_by_index_number", |
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326 "by_header_name", |
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327 "all_but_by_header_name", |
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328 ]: |
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329 c = params["input_options"]["column_selector_options_2"]["col2"] |
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330 else: |
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331 c = None |
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332 |
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333 df_key = infile2 + repr(header) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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334 if df_key in loaded_df: |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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335 infile2 = loaded_df[df_key] |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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336 else: |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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337 infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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338 loaded_df[df_key] = infile2 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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339 |
30
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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340 y = read_columns( |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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341 infile2, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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342 c=c, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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343 c_option=column_option, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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344 sep="\t", |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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345 header=header, |
642452aeed0d
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346 parse_dates=True, |
30
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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347 ) |
24
a152c1d23379
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bgruening
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348 if len(y.shape) == 2 and y.shape[1] == 1: |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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349 y = y.ravel() |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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350 if input_type == "refseq_and_interval": |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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351 estimator.set_params(data_batch_generator__features=y.ravel().tolist()) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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352 y = None |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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353 # end y |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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354 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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355 # load groups |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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356 if groups: |
30
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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357 groups_selector = ( |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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358 params["experiment_schemes"]["test_split"]["split_algos"] |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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359 ).pop("groups_selector") |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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360 |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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361 header = "infer" if groups_selector["header_g"] else None |
30
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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362 column_option = groups_selector["column_selector_options_g"][ |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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|
363 "selected_column_selector_option_g" |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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|
364 ] |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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|
365 if column_option in [ |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff
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|
366 "by_index_number", |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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367 "all_but_by_index_number", |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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368 "by_header_name", |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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369 "all_but_by_header_name", |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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370 ]: |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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371 c = groups_selector["column_selector_options_g"]["col_g"] |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
372 else: |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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373 c = None |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
374 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
375 df_key = groups + repr(header) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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376 if df_key in loaded_df: |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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377 groups = loaded_df[df_key] |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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378 |
30
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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379 groups = read_columns( |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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380 groups, |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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381 c=c, |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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382 c_option=column_option, |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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383 sep="\t", |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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384 header=header, |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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385 parse_dates=True, |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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|
386 ) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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387 groups = groups.ravel() |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
388 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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389 # del loaded_df |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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390 del loaded_df |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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391 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
392 # cache iraps_core fits could increase search speed significantly |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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393 memory = joblib.Memory(location=CACHE_DIR, verbose=0) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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394 main_est = get_main_estimator(estimator) |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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|
395 if main_est.__class__.__name__ == "IRAPSClassifier": |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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|
396 main_est.set_params(memory=memory) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
397 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
398 # handle scorer, convert to scorer dict |
30
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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399 scoring = params["experiment_schemes"]["metrics"]["scoring"] |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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|
400 scorer = get_scoring(scoring) |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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|
401 if not isinstance(scorer, (dict, list)): |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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|
402 scorer = [scoring["primary_scoring"]] |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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|
403 scorer = _check_multimetric_scoring(estimator, scoring=scorer) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
404 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
405 # handle test (first) split |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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|
406 test_split_options = params["experiment_schemes"]["test_split"]["split_algos"] |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
407 |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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|
408 if test_split_options["shuffle"] == "group": |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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|
409 test_split_options["labels"] = groups |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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|
410 if test_split_options["shuffle"] == "stratified": |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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changeset
|
411 if y is not None: |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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|
412 test_split_options["labels"] = y |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
413 else: |
30
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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|
414 raise ValueError( |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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diff
changeset
|
415 "Stratified shuffle split is not " "applicable on empty target values!" |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
|
416 ) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
417 |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
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diff
changeset
|
418 X_train, X_test, y_train, y_test, groups_train, groups_test = train_test_split_none( |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
419 X, y, groups, **test_split_options |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
420 ) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
421 |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
422 exp_scheme = params["experiment_schemes"]["selected_exp_scheme"] |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
423 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
424 # handle validation (second) split |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
425 if exp_scheme == "train_val_test": |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
426 val_split_options = params["experiment_schemes"]["val_split"]["split_algos"] |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
427 |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
428 if val_split_options["shuffle"] == "group": |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
429 val_split_options["labels"] = groups_train |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
430 if val_split_options["shuffle"] == "stratified": |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
431 if y_train is not None: |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
432 val_split_options["labels"] = y_train |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
433 else: |
30
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
|
434 raise ValueError( |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
|
435 "Stratified shuffle split is not " |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
|
436 "applicable on empty target values!" |
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
|
437 ) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
438 |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
439 ( |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
440 X_train, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
441 X_val, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
442 y_train, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
443 y_val, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
444 groups_train, |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
445 groups_val, |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
446 ) = train_test_split_none(X_train, y_train, groups_train, **val_split_options) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
447 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
448 # train and eval |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
449 if hasattr(estimator, "config") and hasattr(estimator, "model_type"): |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
450 if exp_scheme == "train_val_test": |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
451 estimator.fit(X_train, y_train, validation_data=(X_val, y_val)) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
452 else: |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
453 estimator.fit(X_train, y_train, validation_data=(X_test, y_test)) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
454 else: |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
455 estimator.fit(X_train, y_train) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
456 |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
457 if isinstance(estimator, KerasGBatchClassifier): |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
458 scores = {} |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
459 steps = estimator.prediction_steps |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
460 batch_size = estimator.batch_size |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
461 data_generator = estimator.data_generator_ |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
462 |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
463 scores, predictions, y_true = _evaluate_keras_and_sklearn_scores( |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
464 estimator, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
465 data_generator, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
466 X_test, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
467 y=y_test, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
468 sk_scoring=scoring, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
469 steps=steps, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
470 batch_size=batch_size, |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
471 return_predictions=bool(outfile_y_true), |
30
70c5a9127f99
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
|
472 ) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
473 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
474 else: |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
475 scores = {} |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
476 if hasattr(estimator, "model_") and hasattr(estimator.model_, "metrics_names"): |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
477 batch_size = estimator.batch_size |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
478 score_results = estimator.model_.evaluate( |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
479 X_test, y=y_test, batch_size=batch_size, verbose=0 |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
480 ) |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
481 metrics_names = estimator.model_.metrics_names |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
482 if not isinstance(metrics_names, list): |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
483 scores[metrics_names] = score_results |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
484 else: |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
485 scores = dict(zip(metrics_names, score_results)) |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
486 |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
487 if hasattr(estimator, "predict_proba"): |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
488 predictions = estimator.predict_proba(X_test) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
489 else: |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
490 predictions = estimator.predict(X_test) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
491 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
492 y_true = y_test |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
493 sk_scores = _score(estimator, X_test, y_test, scorer) |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
494 scores.update(sk_scores) |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
495 |
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
30
diff
changeset
|
496 # handle output |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
497 if outfile_y_true: |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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498 try: |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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499 pd.DataFrame(y_true).to_csv(outfile_y_true, sep="\t", index=False) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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500 pd.DataFrame(predictions).astype(np.float32).to_csv( |
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0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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501 outfile_y_preds, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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502 sep="\t", |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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503 index=False, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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504 float_format="%g", |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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505 chunksize=10000, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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506 ) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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507 except Exception as e: |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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508 print("Error in saving predictions: %s" % e) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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509 # handle output |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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510 for name, score in scores.items(): |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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511 scores[name] = [score] |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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512 df = pd.DataFrame(scores) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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513 df = df[sorted(df.columns)] |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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514 df.to_csv(path_or_buf=outfile_result, sep="\t", header=True, index=False) |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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515 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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516 memory.clear(warn=False) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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517 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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518 if outfile_object: |
34
642452aeed0d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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519 dump_model_to_h5(estimator, outfile_object) |
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a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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520 |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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521 |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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522 if __name__ == "__main__": |
24
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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523 aparser = argparse.ArgumentParser() |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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524 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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525 aparser.add_argument("-e", "--estimator", dest="infile_estimator") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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526 aparser.add_argument("-X", "--infile1", dest="infile1") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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527 aparser.add_argument("-y", "--infile2", dest="infile2") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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528 aparser.add_argument("-O", "--outfile_result", dest="outfile_result") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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529 aparser.add_argument("-o", "--outfile_object", dest="outfile_object") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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530 aparser.add_argument("-l", "--outfile_y_true", dest="outfile_y_true") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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531 aparser.add_argument("-p", "--outfile_y_preds", dest="outfile_y_preds") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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532 aparser.add_argument("-g", "--groups", dest="groups") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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533 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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534 aparser.add_argument("-b", "--intervals", dest="intervals") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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535 aparser.add_argument("-t", "--targets", dest="targets") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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536 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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537 args = aparser.parse_args() |
a152c1d23379
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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538 |
28
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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539 main( |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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540 args.inputs, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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541 args.infile_estimator, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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542 args.infile1, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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543 args.infile2, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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544 args.outfile_result, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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545 outfile_object=args.outfile_object, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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546 outfile_y_true=args.outfile_y_true, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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547 outfile_y_preds=args.outfile_y_preds, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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548 groups=args.groups, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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549 ref_seq=args.ref_seq, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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550 intervals=args.intervals, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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551 targets=args.targets, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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552 fasta_path=args.fasta_path, |
0cc5098a9bff
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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553 ) |