annotate model_prediction.py @ 0:59e8b4328c82 draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
author bgruening
date Tue, 13 Apr 2021 22:40:10 +0000
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children f93f0cdbaf18
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1 import argparse
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2 import json
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3 import warnings
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4
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5 import numpy as np
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6 import pandas as pd
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7 from galaxy_ml.utils import get_module, load_model, read_columns, try_get_attr
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8 from scipy.io import mmread
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9 from sklearn.pipeline import Pipeline
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11 N_JOBS = int(__import__("os").environ.get("GALAXY_SLOTS", 1))
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12
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14 def main(
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15 inputs,
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16 infile_estimator,
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17 outfile_predict,
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18 infile_weights=None,
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19 infile1=None,
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20 fasta_path=None,
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21 ref_seq=None,
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22 vcf_path=None,
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23 ):
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24 """
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25 Parameter
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26 ---------
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27 inputs : str
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28 File path to galaxy tool parameter
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29
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30 infile_estimator : strgit
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31 File path to trained estimator input
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32
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33 outfile_predict : str
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34 File path to save the prediction results, tabular
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35
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36 infile_weights : str
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37 File path to weights input
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38
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39 infile1 : str
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40 File path to dataset containing features
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41
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42 fasta_path : str
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43 File path to dataset containing fasta file
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44
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45 ref_seq : str
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46 File path to dataset containing the reference genome sequence.
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47
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48 vcf_path : str
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49 File path to dataset containing variants info.
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50 """
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51 warnings.filterwarnings("ignore")
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52
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53 with open(inputs, "r") as param_handler:
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54 params = json.load(param_handler)
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55
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56 # load model
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57 with open(infile_estimator, "rb") as est_handler:
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58 estimator = load_model(est_handler)
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59
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60 main_est = estimator
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61 if isinstance(estimator, Pipeline):
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62 main_est = estimator.steps[-1][-1]
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63 if hasattr(main_est, "config") and hasattr(main_est, "load_weights"):
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64 if not infile_weights or infile_weights == "None":
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65 raise ValueError(
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66 "The selected model skeleton asks for weights, " "but dataset for weights wan not selected!"
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67 )
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68 main_est.load_weights(infile_weights)
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69
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70 # handle data input
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71 input_type = params["input_options"]["selected_input"]
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72 # tabular input
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73 if input_type == "tabular":
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74 header = "infer" if params["input_options"]["header1"] else None
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75 column_option = params["input_options"]["column_selector_options_1"]["selected_column_selector_option"]
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76 if column_option in [
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77 "by_index_number",
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78 "all_but_by_index_number",
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79 "by_header_name",
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80 "all_but_by_header_name",
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81 ]:
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82 c = params["input_options"]["column_selector_options_1"]["col1"]
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83 else:
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84 c = None
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85
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86 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True)
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87
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88 X = read_columns(df, c=c, c_option=column_option).astype(float)
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89
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
90 if params["method"] == "predict":
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
91 preds = estimator.predict(X)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
92 else:
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
93 preds = estimator.predict_proba(X)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
94
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
95 # sparse input
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
96 elif input_type == "sparse":
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
97 X = mmread(open(infile1, "r"))
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
98 if params["method"] == "predict":
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
99 preds = estimator.predict(X)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
100 else:
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
101 preds = estimator.predict_proba(X)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
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102
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
103 # fasta input
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
104 elif input_type == "seq_fasta":
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
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105 if not hasattr(estimator, "data_batch_generator"):
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
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106 raise ValueError(
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
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107 "To do prediction on sequences in fasta input, "
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
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108 "the estimator must be a `KerasGBatchClassifier`"
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
109 "equipped with data_batch_generator!"
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
110 )
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
111 pyfaidx = get_module("pyfaidx")
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
112 sequences = pyfaidx.Fasta(fasta_path)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
113 n_seqs = len(sequences.keys())
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
114 X = np.arange(n_seqs)[:, np.newaxis]
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
115 seq_length = estimator.data_batch_generator.seq_length
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
116 batch_size = getattr(estimator, "batch_size", 32)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
117 steps = (n_seqs + batch_size - 1) // batch_size
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
118
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
119 seq_type = params["input_options"]["seq_type"]
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
120 klass = try_get_attr("galaxy_ml.preprocessors", seq_type)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
121
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
122 pred_data_generator = klass(fasta_path, seq_length=seq_length)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
123
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
124 if params["method"] == "predict":
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
125 preds = estimator.predict(X, data_generator=pred_data_generator, steps=steps)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
126 else:
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
127 preds = estimator.predict_proba(X, data_generator=pred_data_generator, steps=steps)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
128
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
129 # vcf input
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
130 elif input_type == "variant_effect":
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
131 klass = try_get_attr("galaxy_ml.preprocessors", "GenomicVariantBatchGenerator")
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
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132
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
133 options = params["input_options"]
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
134 options.pop("selected_input")
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
135 if options["blacklist_regions"] == "none":
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
136 options["blacklist_regions"] = None
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
137
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
138 pred_data_generator = klass(ref_genome_path=ref_seq, vcf_path=vcf_path, **options)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
139
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
140 pred_data_generator.set_processing_attrs()
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
141
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
142 variants = pred_data_generator.variants
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
143
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
144 # predict 1600 sample at once then write to file
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
145 gen_flow = pred_data_generator.flow(batch_size=1600)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
146
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
147 file_writer = open(outfile_predict, "w")
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
148 header_row = "\t".join(["chrom", "pos", "name", "ref", "alt", "strand"])
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
149 file_writer.write(header_row)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
150 header_done = False
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
151
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
152 steps_done = 0
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
153
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
154 # TODO: multiple threading
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
155 try:
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
156 while steps_done < len(gen_flow):
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
157 index_array = next(gen_flow.index_generator)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
158 batch_X = gen_flow._get_batches_of_transformed_samples(index_array)
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
159
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
160 if params["method"] == "predict":
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
161 batch_preds = estimator.predict(
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
162 batch_X,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
163 # The presence of `pred_data_generator` below is to
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
164 # override model carrying data_generator if there
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
165 # is any.
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
166 data_generator=pred_data_generator,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
167 )
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
168 else:
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
169 batch_preds = estimator.predict_proba(
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
170 batch_X,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
171 # The presence of `pred_data_generator` below is to
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
172 # override model carrying data_generator if there
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
173 # is any.
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
174 data_generator=pred_data_generator,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
175 )
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
176
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
diff changeset
177 if batch_preds.ndim == 1:
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents:
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178 batch_preds = batch_preds[:, np.newaxis]
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179
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180 batch_meta = variants[index_array]
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181 batch_out = np.column_stack([batch_meta, batch_preds])
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182
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183 if not header_done:
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184 heads = np.arange(batch_preds.shape[-1]).astype(str)
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185 heads_str = "\t".join(heads)
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186 file_writer.write("\t%s\n" % heads_str)
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187 header_done = True
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188
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189 for row in batch_out:
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190 row_str = "\t".join(row)
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191 file_writer.write("%s\n" % row_str)
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192
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193 steps_done += 1
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194
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195 finally:
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196 file_writer.close()
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197 # TODO: make api `pred_data_generator.close()`
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198 pred_data_generator.close()
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199 return 0
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200 # end input
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201
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202 # output
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203 if len(preds.shape) == 1:
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204 rval = pd.DataFrame(preds, columns=["Predicted"])
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205 else:
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206 rval = pd.DataFrame(preds)
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207
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208 rval.to_csv(outfile_predict, sep="\t", header=True, index=False)
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209
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210
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211 if __name__ == "__main__":
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212 aparser = argparse.ArgumentParser()
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213 aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
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214 aparser.add_argument("-e", "--infile_estimator", dest="infile_estimator")
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215 aparser.add_argument("-w", "--infile_weights", dest="infile_weights")
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216 aparser.add_argument("-X", "--infile1", dest="infile1")
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217 aparser.add_argument("-O", "--outfile_predict", dest="outfile_predict")
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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218 aparser.add_argument("-f", "--fasta_path", dest="fasta_path")
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219 aparser.add_argument("-r", "--ref_seq", dest="ref_seq")
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220 aparser.add_argument("-v", "--vcf_path", dest="vcf_path")
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221 args = aparser.parse_args()
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222
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223 main(
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224 args.inputs,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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225 args.infile_estimator,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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226 args.outfile_predict,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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227 infile_weights=args.infile_weights,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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228 infile1=args.infile1,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
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229 fasta_path=args.fasta_path,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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230 ref_seq=args.ref_seq,
59e8b4328c82 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
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231 vcf_path=args.vcf_path,
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232 )