comparison pre_process.xml @ 23:792ae8a93b07 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2a058459e6daf0486871f93845f00fdb4a4eaca1

22:315d65cf9e17

import pickle
from scipy.io import mmread
from scipy.io import mmwrite
from sklearn import preprocessing

execfile("$__tool_directory__/utils.py")

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

estimator = my_class(**options)
estimator.fit(X)
result = estimator.transform(X)

#if $input_type.selected_input_type == "sparse":
with open("$outfile_transform", "w+") as transform_handler:
    mmwrite(transform_handler, result)
#else:
res = pandas.DataFrame(result)
res.to_csv(path_or_buf = "$outfile_transform", sep="\t", index=False, header=None)
#end if

23:792ae8a93b07

import pickle
from scipy.io import mmread
from scipy.io import mmwrite
from sklearn import preprocessing

exec(open("$__tool_directory__/utils.py").read(), globals())

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

estimator = my_class(**options)
estimator.fit(X)
result = estimator.transform(X)

#if $input_type.selected_input_type == "sparse":
with open("$outfile_transform", "wb") as transform_handler:
    mmwrite(transform_handler, result)
#else:
res = pandas.DataFrame(result)
res.to_csv(path_or_buf = "$outfile_transform", sep="\t", index=False, header=None)
#end if