Mercurial > repos > bgruening > sklearn_ensemble
comparison ensemble.xml @ 24:e94395c672bd draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
author | bgruening |
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date | Tue, 14 May 2019 18:15:12 -0400 |
parents | 39ae276e75d9 |
children | dde0f1654d18 |
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23:39ae276e75d9 | 24:e94395c672bd |
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12 </command> | 12 </command> |
13 <configfiles> | 13 <configfiles> |
14 <inputs name="inputs"/> | 14 <inputs name="inputs"/> |
15 <configfile name="ensemble_script"> | 15 <configfile name="ensemble_script"> |
16 <![CDATA[ | 16 <![CDATA[ |
17 import sys | |
18 import os | |
19 import json | 17 import json |
20 import numpy as np | 18 import numpy as np |
19 import pandas | |
20 import pickle | |
21 from scipy.io import mmread | |
21 import sklearn.ensemble | 22 import sklearn.ensemble |
22 import pandas | 23 import sys |
23 from scipy.io import mmread | 24 |
24 | 25 sys.path.insert(0, '$__tool_directory__') |
25 with open("$__tool_directory__/sk_whitelist.json", "r") as f: | 26 from utils import load_model, get_X_y |
26 sk_whitelist = json.load(f) | 27 |
27 exec(open("$__tool_directory__/utils.py").read(), globals()) | 28 N_JOBS = int(__import__('os').environ.get('GALAXY_SLOTS', 1)) |
28 | 29 |
29 # Get inputs, outputs. | 30 # Get inputs, outputs. |
30 input_json_path = sys.argv[1] | 31 input_json_path = sys.argv[1] |
31 with open(input_json_path, "r") as param_handler: | 32 with open(input_json_path, "r") as param_handler: |
32 params = json.load(param_handler) | 33 params = json.load(param_handler) |