Repository 'sklearn_generalized_linear'
hg clone https://toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_generalized_linear

Changeset 2:3326dd4f1e8d (2018-03-13)
Previous changeset 1:8e02b727dd74 (2018-02-16) Next changeset 3:be8d2100f07b (2018-03-13)
Commit message:
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 641ac64ded23fbb6fe85d5f13926da12dcce4e76
modified:
generalized_linear.xml
main_macros.xml
b
diff -r 8e02b727dd74 -r 3326dd4f1e8d generalized_linear.xml
--- a/generalized_linear.xml Fri Feb 16 14:57:09 2018 -0500
+++ b/generalized_linear.xml Tue Mar 13 04:58:51 2018 -0400
[
@@ -33,12 +33,24 @@
 options = params["selected_tasks"]["selected_algorithms"]["options"]
 
 #if $selected_tasks.selected_algorithms.input_options.selected_input=="tabular":
-X = columns("$selected_tasks.selected_algorithms.input_options.infile1","$selected_tasks.selected_algorithms.input_options.col1")
+X = read_columns(
+        "$selected_tasks.selected_algorithms.input_options.infile1",
+        "$selected_tasks.selected_algorithms.input_options.col1",
+        sep='\t',
+        header=None,
+        parse_dates=True
+)
 #else:
 X = mmread(open("$selected_tasks.selected_algorithms.input_options.infile1", 'r'))
 #end if
 
-y = columns("$selected_tasks.selected_algorithms.input_options.infile2","$selected_tasks.selected_algorithms.input_options.col2")
+y = read_columns(
+        "$selected_tasks.selected_algorithms.input_options.infile2",
+        "$selected_tasks.selected_algorithms.input_options.col2",
+        sep='\t',
+        header=None,
+        parse_dates=True
+)
 
 my_class = getattr(sklearn.linear_model, algorithm)
 estimator = my_class(**options)
b
diff -r 8e02b727dd74 -r 3326dd4f1e8d main_macros.xml
--- a/main_macros.xml Fri Feb 16 14:57:09 2018 -0500
+++ b/main_macros.xml Tue Mar 13 04:58:51 2018 -0400
b
@@ -2,8 +2,8 @@
   <token name="@VERSION@">0.9</token>
 
   <token name="@COLUMNS_FUNCTION@">
-def columns(f,c):
-  data = pandas.read_csv(f, sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False)
+def read_columns(f, c, **args):
+  data = pandas.read_csv(f, **args)
   cols = c.split (',')
   cols = map(int, cols)
   cols = list(map(lambda x: x - 1, cols))