comparison ensemble.xml @ 28:9eaf13ccab4d draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7

27:5af731ab6995

    </command>
    <configfiles>
        <inputs name="inputs"/>
        <configfile name="ensemble_script">
<![CDATA[
import sys
import os
import json
import numpy as np
import sklearn.ensemble
import pandas
from scipy.io import mmread

with open("$__tool_directory__/sk_whitelist.json", "r") as f:
    sk_whitelist = json.load(f)
exec(open("$__tool_directory__/utils.py").read(), globals())

# Get inputs, outputs.
input_json_path = sys.argv[1]
with open(input_json_path, "r") as param_handler:
    params = json.load(param_handler)

28:9eaf13ccab4d

    </command>
    <configfiles>
        <inputs name="inputs"/>
        <configfile name="ensemble_script">
<![CDATA[
import json
import numpy as np
import pandas
import pickle
from scipy.io import mmread
import sklearn.ensemble
import sys

sys.path.insert(0, '$__tool_directory__')
from utils import load_model, get_X_y

N_JOBS = int(__import__('os').environ.get('GALAXY_SLOTS', 1))

# Get inputs, outputs.
input_json_path = sys.argv[1]
with open(input_json_path, "r") as param_handler:
    params = json.load(param_handler)