Mercurial > repos > bgruening > sklearn_discriminant_classifier
annotate model_prediction.py @ 43:893285b150f8 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 14:33:16 +0000 |
parents | d769d83ec796 |
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rev | line source |
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9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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1 import argparse |
9bb505eafac9
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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eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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3 import warnings |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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4 |
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9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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5 import numpy as np |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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6 import pandas as pd |
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d769d83ec796
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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7 from galaxy_ml.model_persist import load_model_from_h5 |
d769d83ec796
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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8 from galaxy_ml.utils import (clean_params, get_module, read_columns, |
d769d83ec796
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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9 try_get_attr) |
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9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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10 from scipy.io import mmread |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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11 |
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eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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12 N_JOBS = int(__import__("os").environ.get("GALAXY_SLOTS", 1)) |
26
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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13 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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14 |
35
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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15 def main( |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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16 inputs, |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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17 infile_estimator, |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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18 outfile_predict, |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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19 infile1=None, |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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20 fasta_path=None, |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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21 ref_seq=None, |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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22 vcf_path=None, |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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23 ): |
26
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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24 """ |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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25 Parameter |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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26 --------- |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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27 inputs : str |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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28 File path to galaxy tool parameter |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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29 |
41
d769d83ec796
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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30 infile_estimator : str |
26
9bb505eafac9
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 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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32 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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33 outfile_predict : str |
9bb505eafac9
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 save the prediction results, tabular |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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35 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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36 infile1 : str |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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37 File path to dataset containing features |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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38 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 fasta_path : str |
9bb505eafac9
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 dataset containing fasta file |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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41 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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42 ref_seq : str |
9bb505eafac9
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 the reference genome sequence. |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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44 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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45 vcf_path : str |
9bb505eafac9
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 variants info. |
9bb505eafac9
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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eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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48 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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49 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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50 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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51 params = json.load(param_handler) |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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52 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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53 # load model |
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d769d83ec796
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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54 estimator = load_model_from_h5(infile_estimator) |
d769d83ec796
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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55 estimator = clean_params(estimator) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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56 |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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57 # handle data input |
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eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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58 input_type = params["input_options"]["selected_input"] |
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9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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59 # tabular input |
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eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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60 if input_type == "tabular": |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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61 header = "infer" if params["input_options"]["header1"] else None |
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e76f6dfea5c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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62 column_option = params["input_options"]["column_selector_options_1"][ |
e76f6dfea5c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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63 "selected_column_selector_option" |
e76f6dfea5c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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64 ] |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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65 if column_option in [ |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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66 "by_index_number", |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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67 "all_but_by_index_number", |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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68 "by_header_name", |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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69 "all_but_by_header_name", |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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70 ]: |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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71 c = params["input_options"]["column_selector_options_1"]["col1"] |
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72 else: |
9bb505eafac9
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73 c = None |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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74 |
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eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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75 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True) |
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76 |
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77 X = read_columns(df, c=c, c_option=column_option).astype(float) |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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78 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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79 if params["method"] == "predict": |
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80 preds = estimator.predict(X) |
9bb505eafac9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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81 else: |
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82 preds = estimator.predict_proba(X) |
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83 |
9bb505eafac9
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84 # sparse input |
35
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85 elif input_type == "sparse": |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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86 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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87 if params["method"] == "predict": |
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88 preds = estimator.predict(X) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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89 else: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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90 preds = estimator.predict_proba(X) |
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91 |
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92 # fasta input |
35
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93 elif input_type == "seq_fasta": |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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94 if not hasattr(estimator, "data_batch_generator"): |
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95 raise ValueError( |
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96 "To do prediction on sequences in fasta input, " |
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97 "the estimator must be a `KerasGBatchClassifier`" |
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98 "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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99 ) |
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100 pyfaidx = get_module("pyfaidx") |
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101 sequences = pyfaidx.Fasta(fasta_path) |
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102 n_seqs = len(sequences.keys()) |
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103 X = np.arange(n_seqs)[:, np.newaxis] |
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104 seq_length = estimator.data_batch_generator.seq_length |
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105 batch_size = getattr(estimator, "batch_size", 32) |
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106 steps = (n_seqs + batch_size - 1) // batch_size |
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107 |
35
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108 seq_type = params["input_options"]["seq_type"] |
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109 klass = try_get_attr("galaxy_ml.preprocessors", seq_type) |
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110 |
35
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111 pred_data_generator = klass(fasta_path, seq_length=seq_length) |
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112 |
35
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113 if params["method"] == "predict": |
37
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114 preds = estimator.predict( |
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115 X, data_generator=pred_data_generator, steps=steps |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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116 ) |
26
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117 else: |
37
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118 preds = estimator.predict_proba( |
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119 X, data_generator=pred_data_generator, steps=steps |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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120 ) |
26
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121 |
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122 # vcf input |
35
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123 elif input_type == "variant_effect": |
eeaf989f1024
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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124 klass = try_get_attr("galaxy_ml.preprocessors", "GenomicVariantBatchGenerator") |
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125 |
35
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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126 options = params["input_options"] |
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127 options.pop("selected_input") |
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128 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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129 options["blacklist_regions"] = None |
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130 |
37
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131 pred_data_generator = klass( |
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132 ref_genome_path=ref_seq, vcf_path=vcf_path, **options |
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133 ) |
26
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134 |
31
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135 pred_data_generator.set_processing_attrs() |
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136 |
27
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137 variants = pred_data_generator.variants |
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138 |
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139 # predict 1600 sample at once then write to file |
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140 gen_flow = pred_data_generator.flow(batch_size=1600) |
8e49f26b14d3
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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141 |
35
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142 file_writer = open(outfile_predict, "w") |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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143 header_row = "\t".join(["chrom", "pos", "name", "ref", "alt", "strand"]) |
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144 file_writer.write(header_row) |
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145 header_done = False |
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146 |
27
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147 steps_done = 0 |
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148 |
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149 # TODO: multiple threading |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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150 try: |
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151 while steps_done < len(gen_flow): |
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152 index_array = next(gen_flow.index_generator) |
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153 batch_X = gen_flow._get_batches_of_transformed_samples(index_array) |
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154 |
35
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155 if params["method"] == "predict": |
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156 batch_preds = estimator.predict( |
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157 batch_X, |
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158 # The presence of `pred_data_generator` below is to |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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159 # override model carrying data_generator if there |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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160 # is any. |
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161 data_generator=pred_data_generator, |
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162 ) |
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163 else: |
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164 batch_preds = estimator.predict_proba( |
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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 |
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172 if batch_preds.ndim == 1: |
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173 batch_preds = batch_preds[:, np.newaxis] |
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174 |
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175 batch_meta = variants[index_array] |
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176 batch_out = np.column_stack([batch_meta, batch_preds]) |
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177 |
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178 if not header_done: |
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179 heads = np.arange(batch_preds.shape[-1]).astype(str) |
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180 heads_str = "\t".join(heads) |
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181 file_writer.write("\t%s\n" % heads_str) |
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182 header_done = True |
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183 |
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184 for row in batch_out: |
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185 row_str = "\t".join(row) |
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186 file_writer.write("%s\n" % row_str) |
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187 |
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188 steps_done += 1 |
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189 |
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190 finally: |
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191 file_writer.close() |
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192 # TODO: make api `pred_data_generator.close()` |
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193 pred_data_generator.close() |
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194 return 0 |
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195 # end input |
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196 |
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197 # output |
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198 if len(preds.shape) == 1: |
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199 rval = pd.DataFrame(preds, columns=["Predicted"]) |
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200 else: |
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201 rval = pd.DataFrame(preds) |
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202 |
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203 rval.to_csv(outfile_predict, sep="\t", header=True, index=False) |
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204 |
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205 |
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206 if __name__ == "__main__": |
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207 aparser = argparse.ArgumentParser() |
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208 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
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209 aparser.add_argument("-e", "--infile_estimator", dest="infile_estimator") |
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210 aparser.add_argument("-X", "--infile1", dest="infile1") |
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211 aparser.add_argument("-O", "--outfile_predict", dest="outfile_predict") |
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212 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
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213 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
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214 aparser.add_argument("-v", "--vcf_path", dest="vcf_path") |
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215 args = aparser.parse_args() |
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216 |
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217 main( |
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218 args.inputs, |
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219 args.infile_estimator, |
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220 args.outfile_predict, |
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221 infile1=args.infile1, |
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222 fasta_path=args.fasta_path, |
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223 ref_seq=args.ref_seq, |
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224 vcf_path=args.vcf_path, |
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225 ) |