Mercurial > repos > bgruening > sklearn_clf_metrics
annotate model_prediction.py @ 38:daaa56720686 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d970dae980fbe349414fc0889f719d875d999c5b"
author | bgruening |
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date | Fri, 27 Aug 2021 10:22:56 +0000 |
parents | c8547d3993c0 |
children | e3c787437a6d |
rev | line source |
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44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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1 import argparse |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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2 import json |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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3 import warnings |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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4 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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5 import numpy as np |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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6 import pandas as pd |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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7 from galaxy_ml.utils import get_module, load_model, read_columns, try_get_attr |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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8 from scipy.io import mmread |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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9 from sklearn.pipeline import Pipeline |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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10 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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11 N_JOBS = int(__import__("os").environ.get("GALAXY_SLOTS", 1)) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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12 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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13 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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14 def main( |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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15 inputs, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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16 infile_estimator, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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17 outfile_predict, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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18 infile_weights=None, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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19 infile1=None, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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20 fasta_path=None, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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21 ref_seq=None, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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22 vcf_path=None, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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23 ): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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24 """ |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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25 Parameter |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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26 --------- |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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27 inputs : str |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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28 File path to galaxy tool parameter |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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29 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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30 infile_estimator : strgit |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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31 File path to trained estimator input |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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32 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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33 outfile_predict : str |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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34 File path to save the prediction results, tabular |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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35 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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36 infile_weights : str |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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37 File path to weights input |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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38 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 infile1 : str |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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40 File path to dataset containing features |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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41 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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42 fasta_path : str |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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43 File path to dataset containing fasta file |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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44 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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45 ref_seq : str |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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46 File path to dataset containing the reference genome sequence. |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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47 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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48 vcf_path : str |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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49 File path to dataset containing variants info. |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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50 """ |
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51 warnings.filterwarnings("ignore") |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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52 |
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53 with open(inputs, "r") as param_handler: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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54 params = json.load(param_handler) |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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55 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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56 # load model |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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57 with open(infile_estimator, "rb") as est_handler: |
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58 estimator = load_model(est_handler) |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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59 |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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60 main_est = estimator |
44f0ce9488fb
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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61 if isinstance(estimator, Pipeline): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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62 main_est = estimator.steps[-1][-1] |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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63 if hasattr(main_est, "config") and hasattr(main_est, "load_weights"): |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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64 if not infile_weights or infile_weights == "None": |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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65 raise ValueError( |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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66 "The selected model skeleton asks for weights, " |
c8547d3993c0
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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67 "but dataset for weights wan not selected!" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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68 ) |
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69 main_est.load_weights(infile_weights) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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70 |
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71 # handle data input |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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72 input_type = params["input_options"]["selected_input"] |
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73 # tabular input |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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74 if input_type == "tabular": |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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75 header = "infer" if params["input_options"]["header1"] else None |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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76 column_option = params["input_options"]["column_selector_options_1"][ |
c8547d3993c0
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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77 "selected_column_selector_option" |
c8547d3993c0
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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78 ] |
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79 if column_option in [ |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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80 "by_index_number", |
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81 "all_but_by_index_number", |
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82 "by_header_name", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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83 "all_but_by_header_name", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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84 ]: |
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85 c = params["input_options"]["column_selector_options_1"]["col1"] |
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86 else: |
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87 c = None |
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88 |
35
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89 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True) |
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90 |
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91 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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92 |
35
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93 if params["method"] == "predict": |
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94 preds = estimator.predict(X) |
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95 else: |
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96 preds = estimator.predict_proba(X) |
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97 |
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98 # sparse input |
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99 elif input_type == "sparse": |
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100 X = mmread(open(infile1, "r")) |
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101 if params["method"] == "predict": |
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102 preds = estimator.predict(X) |
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103 else: |
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104 preds = estimator.predict_proba(X) |
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105 |
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106 # fasta input |
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107 elif input_type == "seq_fasta": |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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108 if not hasattr(estimator, "data_batch_generator"): |
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109 raise ValueError( |
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110 "To do prediction on sequences in fasta input, " |
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111 "the estimator must be a `KerasGBatchClassifier`" |
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112 "equipped with data_batch_generator!" |
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113 ) |
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114 pyfaidx = get_module("pyfaidx") |
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115 sequences = pyfaidx.Fasta(fasta_path) |
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116 n_seqs = len(sequences.keys()) |
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117 X = np.arange(n_seqs)[:, np.newaxis] |
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118 seq_length = estimator.data_batch_generator.seq_length |
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119 batch_size = getattr(estimator, "batch_size", 32) |
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120 steps = (n_seqs + batch_size - 1) // batch_size |
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121 |
35
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122 seq_type = params["input_options"]["seq_type"] |
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123 klass = try_get_attr("galaxy_ml.preprocessors", seq_type) |
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124 |
35
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125 pred_data_generator = klass(fasta_path, seq_length=seq_length) |
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126 |
35
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127 if params["method"] == "predict": |
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128 preds = estimator.predict( |
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129 X, data_generator=pred_data_generator, steps=steps |
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130 ) |
26
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131 else: |
37
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132 preds = estimator.predict_proba( |
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133 X, data_generator=pred_data_generator, steps=steps |
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134 ) |
26
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135 |
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136 # vcf input |
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137 elif input_type == "variant_effect": |
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138 klass = try_get_attr("galaxy_ml.preprocessors", "GenomicVariantBatchGenerator") |
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139 |
35
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140 options = params["input_options"] |
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141 options.pop("selected_input") |
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142 if options["blacklist_regions"] == "none": |
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143 options["blacklist_regions"] = None |
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144 |
37
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145 pred_data_generator = klass( |
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146 ref_genome_path=ref_seq, vcf_path=vcf_path, **options |
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147 ) |
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148 |
31
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149 pred_data_generator.set_processing_attrs() |
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150 |
27
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151 variants = pred_data_generator.variants |
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152 |
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153 # predict 1600 sample at once then write to file |
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154 gen_flow = pred_data_generator.flow(batch_size=1600) |
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155 |
35
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156 file_writer = open(outfile_predict, "w") |
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157 header_row = "\t".join(["chrom", "pos", "name", "ref", "alt", "strand"]) |
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158 file_writer.write(header_row) |
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159 header_done = False |
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160 |
27
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161 steps_done = 0 |
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162 |
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163 # TODO: multiple threading |
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164 try: |
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165 while steps_done < len(gen_flow): |
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166 index_array = next(gen_flow.index_generator) |
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167 batch_X = gen_flow._get_batches_of_transformed_samples(index_array) |
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168 |
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169 if params["method"] == "predict": |
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170 batch_preds = estimator.predict( |
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171 batch_X, |
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172 # The presence of `pred_data_generator` below is to |
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173 # override model carrying data_generator if there |
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174 # is any. |
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175 data_generator=pred_data_generator, |
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176 ) |
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177 else: |
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178 batch_preds = estimator.predict_proba( |
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179 batch_X, |
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180 # The presence of `pred_data_generator` below is to |
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181 # override model carrying data_generator if there |
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182 # is any. |
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183 data_generator=pred_data_generator, |
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184 ) |
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185 |
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186 if batch_preds.ndim == 1: |
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187 batch_preds = batch_preds[:, np.newaxis] |
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188 |
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189 batch_meta = variants[index_array] |
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190 batch_out = np.column_stack([batch_meta, batch_preds]) |
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191 |
27
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192 if not header_done: |
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193 heads = np.arange(batch_preds.shape[-1]).astype(str) |
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194 heads_str = "\t".join(heads) |
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195 file_writer.write("\t%s\n" % heads_str) |
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196 header_done = True |
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197 |
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198 for row in batch_out: |
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199 row_str = "\t".join(row) |
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200 file_writer.write("%s\n" % row_str) |
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201 |
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202 steps_done += 1 |
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203 |
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204 finally: |
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205 file_writer.close() |
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206 # TODO: make api `pred_data_generator.close()` |
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207 pred_data_generator.close() |
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208 return 0 |
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209 # end input |
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210 |
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211 # output |
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212 if len(preds.shape) == 1: |
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213 rval = pd.DataFrame(preds, columns=["Predicted"]) |
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214 else: |
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215 rval = pd.DataFrame(preds) |
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216 |
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217 rval.to_csv(outfile_predict, sep="\t", header=True, index=False) |
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218 |
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219 |
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220 if __name__ == "__main__": |
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221 aparser = argparse.ArgumentParser() |
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222 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
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223 aparser.add_argument("-e", "--infile_estimator", dest="infile_estimator") |
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224 aparser.add_argument("-w", "--infile_weights", dest="infile_weights") |
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225 aparser.add_argument("-X", "--infile1", dest="infile1") |
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226 aparser.add_argument("-O", "--outfile_predict", dest="outfile_predict") |
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227 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
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228 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
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229 aparser.add_argument("-v", "--vcf_path", dest="vcf_path") |
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230 args = aparser.parse_args() |
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231 |
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232 main( |
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233 args.inputs, |
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234 args.infile_estimator, |
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235 args.outfile_predict, |
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236 infile_weights=args.infile_weights, |
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237 infile1=args.infile1, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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238 fasta_path=args.fasta_path, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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31
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changeset
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239 ref_seq=args.ref_seq, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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31
diff
changeset
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240 vcf_path=args.vcf_path, |
388f6ec0f3b3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
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241 ) |