Mercurial > repos > bgruening > keras_model_config
annotate model_prediction.py @ 2:bedbda03c573 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
author | bgruening |
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date | Wed, 02 Oct 2019 03:53:02 -0400 |
parents | 0fd7d8e90e2a |
children | c3813c64d678 |
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1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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1 import argparse |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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2 import json |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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3 import numpy as np |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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4 import pandas as pd |
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0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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5 import tabix |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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6 import warnings |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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7 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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8 from scipy.io import mmread |
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9 from sklearn.pipeline import Pipeline |
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10 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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11 from galaxy_ml.externals.selene_sdk.sequences import Genome |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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12 from galaxy_ml.utils import (load_model, read_columns, |
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13 get_module, try_get_attr) |
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14 |
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15 |
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16 N_JOBS = int(__import__('os').environ.get('GALAXY_SLOTS', 1)) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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17 |
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18 |
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19 def main(inputs, infile_estimator, outfile_predict, |
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20 infile_weights=None, infile1=None, |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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21 fasta_path=None, ref_seq=None, |
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22 vcf_path=None): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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23 """ |
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24 Parameter |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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25 --------- |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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26 inputs : str |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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27 File path to galaxy tool parameter |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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28 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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29 infile_estimator : strgit |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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30 File path to trained estimator input |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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31 |
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32 outfile_predict : str |
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33 File path to save the prediction results, tabular |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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34 |
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35 infile_weights : str |
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36 File path to weights input |
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37 |
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38 infile1 : str |
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39 File path to dataset containing features |
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40 |
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41 fasta_path : str |
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42 File path to dataset containing fasta file |
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43 |
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44 ref_seq : str |
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45 File path to dataset containing the reference genome sequence. |
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46 |
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47 vcf_path : str |
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48 File path to dataset containing variants info. |
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49 """ |
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50 warnings.filterwarnings('ignore') |
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51 |
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52 with open(inputs, 'r') as param_handler: |
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53 params = json.load(param_handler) |
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54 |
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55 # load model |
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56 with open(infile_estimator, 'rb') as est_handler: |
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57 estimator = load_model(est_handler) |
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58 |
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59 main_est = estimator |
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60 if isinstance(estimator, Pipeline): |
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61 main_est = estimator.steps[-1][-1] |
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62 if hasattr(main_est, 'config') and hasattr(main_est, 'load_weights'): |
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63 if not infile_weights or infile_weights == 'None': |
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64 raise ValueError("The selected model skeleton asks for weights, " |
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65 "but dataset for weights wan not selected!") |
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66 main_est.load_weights(infile_weights) |
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67 |
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68 # handle data input |
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69 input_type = params['input_options']['selected_input'] |
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70 # tabular input |
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71 if input_type == 'tabular': |
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72 header = 'infer' if params['input_options']['header1'] else None |
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73 column_option = (params['input_options'] |
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74 ['column_selector_options_1'] |
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75 ['selected_column_selector_option']) |
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76 if column_option in ['by_index_number', 'all_but_by_index_number', |
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77 'by_header_name', 'all_but_by_header_name']: |
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78 c = params['input_options']['column_selector_options_1']['col1'] |
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79 else: |
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80 c = None |
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81 |
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82 df = pd.read_csv(infile1, sep='\t', header=header, parse_dates=True) |
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83 |
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84 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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85 |
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86 if params['method'] == 'predict': |
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87 preds = estimator.predict(X) |
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88 else: |
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89 preds = estimator.predict_proba(X) |
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90 |
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91 # sparse input |
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92 elif input_type == 'sparse': |
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93 X = mmread(open(infile1, 'r')) |
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94 if params['method'] == 'predict': |
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95 preds = estimator.predict(X) |
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96 else: |
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97 preds = estimator.predict_proba(X) |
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98 |
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99 # fasta input |
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100 elif input_type == 'seq_fasta': |
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101 if not hasattr(estimator, 'data_batch_generator'): |
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102 raise ValueError( |
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103 "To do prediction on sequences in fasta input, " |
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104 "the estimator must be a `KerasGBatchClassifier`" |
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105 "equipped with data_batch_generator!") |
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106 pyfaidx = get_module('pyfaidx') |
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107 sequences = pyfaidx.Fasta(fasta_path) |
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108 n_seqs = len(sequences.keys()) |
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109 X = np.arange(n_seqs)[:, np.newaxis] |
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110 seq_length = estimator.data_batch_generator.seq_length |
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111 batch_size = getattr(estimator, 'batch_size', 32) |
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112 steps = (n_seqs + batch_size - 1) // batch_size |
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113 |
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114 seq_type = params['input_options']['seq_type'] |
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115 klass = try_get_attr( |
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116 'galaxy_ml.preprocessors', seq_type) |
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117 |
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118 pred_data_generator = klass( |
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119 fasta_path, seq_length=seq_length) |
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120 |
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121 if params['method'] == 'predict': |
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122 preds = estimator.predict( |
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123 X, data_generator=pred_data_generator, steps=steps) |
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124 else: |
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125 preds = estimator.predict_proba( |
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126 X, data_generator=pred_data_generator, steps=steps) |
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127 |
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128 # vcf input |
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129 elif input_type == 'variant_effect': |
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130 klass = try_get_attr('galaxy_ml.preprocessors', |
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131 'GenomicVariantBatchGenerator') |
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132 |
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133 options = params['input_options'] |
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134 options.pop('selected_input') |
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135 if options['blacklist_regions'] == 'none': |
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136 options['blacklist_regions'] = None |
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137 |
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138 pred_data_generator = klass( |
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139 ref_genome_path=ref_seq, vcf_path=vcf_path, **options) |
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140 |
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141 pred_data_generator.fit() |
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142 |
1
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143 variants = pred_data_generator.variants |
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144 # TODO : remove the following block after galaxy-ml v0.7.13 |
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145 blacklist_tabix = getattr(pred_data_generator.reference_genome_, |
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146 '_blacklist_tabix', None) |
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147 clean_variants = [] |
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148 if blacklist_tabix: |
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149 start_radius = pred_data_generator.start_radius_ |
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150 end_radius = pred_data_generator.end_radius_ |
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151 |
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152 for chrom, pos, name, ref, alt, strand in variants: |
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153 center = pos + len(ref) // 2 |
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154 start = center - start_radius |
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155 end = center + end_radius |
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156 |
1
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157 if isinstance(pred_data_generator.reference_genome_, Genome): |
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158 if "chr" not in chrom: |
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159 chrom = "chr" + chrom |
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160 if "MT" in chrom: |
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161 chrom = chrom[:-1] |
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162 try: |
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163 rows = blacklist_tabix.query(chrom, start, end) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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164 found = 0 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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165 for row in rows: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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166 found = 1 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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|
167 break |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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|
168 if found: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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|
169 continue |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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170 except tabix.TabixError: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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|
171 pass |
0
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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172 |
1
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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173 clean_variants.append((chrom, pos, name, ref, alt, strand)) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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174 else: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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175 clean_variants = variants |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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176 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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177 setattr(pred_data_generator, 'variants', clean_variants) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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178 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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179 variants = np.array(clean_variants) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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180 # predict 1600 sample at once then write to file |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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181 gen_flow = pred_data_generator.flow(batch_size=1600) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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182 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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183 file_writer = open(outfile_predict, 'w') |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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184 header_row = '\t'.join(['chrom', 'pos', 'name', 'ref', |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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185 'alt', 'strand']) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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186 file_writer.write(header_row) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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187 header_done = False |
0
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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188 |
1
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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189 steps_done = 0 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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190 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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191 # TODO: multiple threading |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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192 try: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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193 while steps_done < len(gen_flow): |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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194 index_array = next(gen_flow.index_generator) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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195 batch_X = gen_flow._get_batches_of_transformed_samples( |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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196 index_array) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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197 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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198 if params['method'] == 'predict': |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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199 batch_preds = estimator.predict( |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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200 batch_X, |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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201 # The presence of `pred_data_generator` below is to |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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202 # override model carrying data_generator if there |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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203 # is any. |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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204 data_generator=pred_data_generator) |
0
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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205 else: |
1
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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206 batch_preds = estimator.predict_proba( |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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207 batch_X, |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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208 # The presence of `pred_data_generator` below is to |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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209 # override model carrying data_generator if there |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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210 # is any. |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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211 data_generator=pred_data_generator) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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212 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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213 if batch_preds.ndim == 1: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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214 batch_preds = batch_preds[:, np.newaxis] |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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215 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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216 batch_meta = variants[index_array] |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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217 batch_out = np.column_stack([batch_meta, batch_preds]) |
0
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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218 |
1
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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219 if not header_done: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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220 heads = np.arange(batch_preds.shape[-1]).astype(str) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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221 heads_str = '\t'.join(heads) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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222 file_writer.write("\t%s\n" % heads_str) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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223 header_done = True |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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224 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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225 for row in batch_out: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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226 row_str = '\t'.join(row) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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227 file_writer.write("%s\n" % row_str) |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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228 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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229 steps_done += 1 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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230 |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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231 finally: |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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232 file_writer.close() |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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233 # TODO: make api `pred_data_generator.close()` |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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234 pred_data_generator.close() |
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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235 return 0 |
0
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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236 # end input |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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237 |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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238 # output |
1
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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239 if len(preds.shape) == 1: |
0
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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240 rval = pd.DataFrame(preds, columns=['Predicted']) |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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241 else: |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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242 rval = pd.DataFrame(preds) |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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243 |
1
0fd7d8e90e2a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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244 rval.to_csv(outfile_predict, sep='\t', header=True, index=False) |
0
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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245 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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246 |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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247 if __name__ == '__main__': |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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248 aparser = argparse.ArgumentParser() |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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249 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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250 aparser.add_argument("-e", "--infile_estimator", dest="infile_estimator") |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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251 aparser.add_argument("-w", "--infile_weights", dest="infile_weights") |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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252 aparser.add_argument("-X", "--infile1", dest="infile1") |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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253 aparser.add_argument("-O", "--outfile_predict", dest="outfile_predict") |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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254 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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255 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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256 aparser.add_argument("-v", "--vcf_path", dest="vcf_path") |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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257 args = aparser.parse_args() |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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258 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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259 main(args.inputs, args.infile_estimator, args.outfile_predict, |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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260 infile_weights=args.infile_weights, infile1=args.infile1, |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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261 fasta_path=args.fasta_path, ref_seq=args.ref_seq, |
1046cf73236b
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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262 vcf_path=args.vcf_path) |