Mercurial > repos > bgruening > sklearn_build_pipeline
annotate model_prediction.py @ 19:4de3d598c116 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
author | bgruening |
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date | Tue, 13 Apr 2021 18:57:31 +0000 |
parents | 3f3c6dc38f3e |
children | 664666bd14ec |
rev | line source |
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775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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1 import argparse |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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2 import json |
19
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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3 import warnings |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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4 |
10
775b004b7920
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 |
775b004b7920
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 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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7 from scipy.io import mmread |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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8 from sklearn.pipeline import Pipeline |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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9 |
19
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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10 from galaxy_ml.utils import (get_module, load_model, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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11 read_columns, try_get_attr) |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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12 |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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13 |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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14 N_JOBS = int(__import__("os").environ.get("GALAXY_SLOTS", 1)) |
10
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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15 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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16 |
19
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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17 def main( |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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18 inputs, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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19 infile_estimator, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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20 outfile_predict, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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21 infile_weights=None, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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22 infile1=None, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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23 fasta_path=None, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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24 ref_seq=None, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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25 vcf_path=None, |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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26 ): |
10
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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27 """ |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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28 Parameter |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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29 --------- |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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30 inputs : str |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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31 File path to galaxy tool parameter |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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32 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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33 infile_estimator : strgit |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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34 File path to trained estimator input |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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35 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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36 outfile_predict : str |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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37 File path to save the prediction results, tabular |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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38 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 infile_weights : str |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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40 File path to weights input |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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41 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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42 infile1 : str |
775b004b7920
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 features |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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44 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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45 fasta_path : str |
775b004b7920
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 fasta file |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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47 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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48 ref_seq : str |
775b004b7920
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 the reference genome sequence. |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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50 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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51 vcf_path : str |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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52 File path to dataset containing variants info. |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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53 """ |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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54 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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55 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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56 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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57 params = json.load(param_handler) |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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58 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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59 # load model |
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4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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60 with open(infile_estimator, "rb") as est_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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61 estimator = load_model(est_handler) |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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62 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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63 main_est = estimator |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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64 if isinstance(estimator, Pipeline): |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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65 main_est = estimator.steps[-1][-1] |
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4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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66 if hasattr(main_est, "config") and hasattr(main_est, "load_weights"): |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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67 if not infile_weights or infile_weights == "None": |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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68 raise ValueError( |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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69 "The selected model skeleton asks for weights, " "but dataset for weights wan not selected!" |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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70 ) |
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71 main_est.load_weights(infile_weights) |
775b004b7920
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72 |
775b004b7920
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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73 # 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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74 input_type = params["input_options"]["selected_input"] |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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75 # tabular input |
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4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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76 if input_type == "tabular": |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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77 header = "infer" if params["input_options"]["header1"] else None |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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78 column_option = params["input_options"]["column_selector_options_1"]["selected_column_selector_option"] |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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79 if column_option in [ |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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80 "by_index_number", |
4de3d598c116
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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81 "all_but_by_index_number", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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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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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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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 |
19
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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 |
19
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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 |
19
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99 elif input_type == "sparse": |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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100 X = mmread(open(infile1, "r")) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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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 |
19
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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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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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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112 "equipped with data_batch_generator!" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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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 |
19
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122 seq_type = params["input_options"]["seq_type"] |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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123 klass = try_get_attr("galaxy_ml.preprocessors", seq_type) |
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124 |
19
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125 pred_data_generator = klass(fasta_path, seq_length=seq_length) |
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126 |
19
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127 if params["method"] == "predict": |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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128 preds = estimator.predict(X, data_generator=pred_data_generator, steps=steps) |
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129 else: |
19
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130 preds = estimator.predict_proba(X, data_generator=pred_data_generator, steps=steps) |
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131 |
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132 # vcf input |
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133 elif input_type == "variant_effect": |
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134 klass = try_get_attr("galaxy_ml.preprocessors", "GenomicVariantBatchGenerator") |
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135 |
19
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136 options = params["input_options"] |
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137 options.pop("selected_input") |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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138 if options["blacklist_regions"] == "none": |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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139 options["blacklist_regions"] = None |
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140 |
19
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141 pred_data_generator = klass(ref_genome_path=ref_seq, vcf_path=vcf_path, **options) |
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142 |
15
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143 pred_data_generator.set_processing_attrs() |
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144 |
11
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145 variants = pred_data_generator.variants |
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146 |
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147 # predict 1600 sample at once then write to file |
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148 gen_flow = pred_data_generator.flow(batch_size=1600) |
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149 |
19
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150 file_writer = open(outfile_predict, "w") |
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151 header_row = "\t".join(["chrom", "pos", "name", "ref", "alt", "strand"]) |
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152 file_writer.write(header_row) |
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153 header_done = False |
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154 |
11
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155 steps_done = 0 |
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156 |
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157 # TODO: multiple threading |
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158 try: |
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159 while steps_done < len(gen_flow): |
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160 index_array = next(gen_flow.index_generator) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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161 batch_X = gen_flow._get_batches_of_transformed_samples(index_array) |
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162 |
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163 if params["method"] == "predict": |
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164 batch_preds = estimator.predict( |
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165 batch_X, |
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166 # The presence of `pred_data_generator` below is to |
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167 # override model carrying data_generator if there |
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168 # is any. |
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169 data_generator=pred_data_generator, |
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170 ) |
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171 else: |
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172 batch_preds = estimator.predict_proba( |
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173 batch_X, |
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174 # The presence of `pred_data_generator` below is to |
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175 # override model carrying data_generator if there |
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176 # is any. |
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177 data_generator=pred_data_generator, |
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178 ) |
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179 |
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180 if batch_preds.ndim == 1: |
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181 batch_preds = batch_preds[:, np.newaxis] |
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182 |
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183 batch_meta = variants[index_array] |
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184 batch_out = np.column_stack([batch_meta, batch_preds]) |
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185 |
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186 if not header_done: |
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187 heads = np.arange(batch_preds.shape[-1]).astype(str) |
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188 heads_str = "\t".join(heads) |
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189 file_writer.write("\t%s\n" % heads_str) |
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190 header_done = True |
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191 |
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192 for row in batch_out: |
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193 row_str = "\t".join(row) |
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194 file_writer.write("%s\n" % row_str) |
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195 |
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196 steps_done += 1 |
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197 |
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198 finally: |
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199 file_writer.close() |
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200 # TODO: make api `pred_data_generator.close()` |
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201 pred_data_generator.close() |
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202 return 0 |
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203 # end input |
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204 |
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205 # output |
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206 if len(preds.shape) == 1: |
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207 rval = pd.DataFrame(preds, columns=["Predicted"]) |
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208 else: |
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209 rval = pd.DataFrame(preds) |
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210 |
19
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211 rval.to_csv(outfile_predict, sep="\t", header=True, index=False) |
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212 |
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213 |
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214 if __name__ == "__main__": |
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215 aparser = argparse.ArgumentParser() |
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216 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
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217 aparser.add_argument("-e", "--infile_estimator", dest="infile_estimator") |
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218 aparser.add_argument("-w", "--infile_weights", dest="infile_weights") |
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219 aparser.add_argument("-X", "--infile1", dest="infile1") |
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220 aparser.add_argument("-O", "--outfile_predict", dest="outfile_predict") |
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221 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
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222 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
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223 aparser.add_argument("-v", "--vcf_path", dest="vcf_path") |
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224 args = aparser.parse_args() |
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225 |
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226 main( |
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227 args.inputs, |
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228 args.infile_estimator, |
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229 args.outfile_predict, |
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230 infile_weights=args.infile_weights, |
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231 infile1=args.infile1, |
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232 fasta_path=args.fasta_path, |
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233 ref_seq=args.ref_seq, |
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234 vcf_path=args.vcf_path, |
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235 ) |