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

Changeset 7:82f51b60c4ee (2018-04-28)
Previous changeset 6:961e9696f3d8 (2018-04-12) Next changeset 8:08d81a5ec1e8 (2018-05-22)
Commit message:
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
modified:
clf_metrics.xml
main_macros.xml
added:
test-data/mv_result01.tabular
test-data/mv_result02.tabular
test-data/mv_result03.tabular
test-data/mv_result04.tabular
test-data/mv_result05.tabular
test-data/mv_result06.tabular
test-data/regression_metrics_result01
test-data/regression_metrics_result02
test-data/regression_metrics_result03
test-data/regression_metrics_result04
test-data/regression_metrics_result05
test-data/regression_metrics_result06
test-data/regression_test_y.tabular
b
diff -r 961e9696f3d8 -r 82f51b60c4ee clf_metrics.xml
--- a/clf_metrics.xml Thu Apr 12 08:24:10 2018 -0400
+++ b/clf_metrics.xml Sat Apr 28 18:09:19 2018 -0400
[
@@ -26,19 +26,21 @@
 input_json_path = sys.argv[1]
 params = json.load(open(input_json_path, "r"))
 
-
+header='infer' if params["clf_metrics"].get("header1", None) else None
 y_t = read_columns(
         "$clf_metrics.infile1",
         "$clf_metrics.col1",
         sep='\t',
-        header=None,
+        header=header,
         parse_dates=True
 )
+
+header='infer' if params["clf_metrics"].get("header2", None) else None
 y_p = read_columns(
         "$clf_metrics.infile2",
         "$clf_metrics.col2",
         sep='\t',
-        header=None,
+        header=header,
         parse_dates=True
 )
 
b
diff -r 961e9696f3d8 -r 82f51b60c4ee main_macros.xml
--- a/main_macros.xml Thu Apr 12 08:24:10 2018 -0400
+++ b/main_macros.xml Sat Apr 28 18:09:19 2018 -0400
b
@@ -423,8 +423,10 @@
 
   <xml name="clf_inputs" token_label1="Dataset containing true labels (tabular):" token_label2="Dataset containing predicted values (tabular):" token_multiple1="False" token_multiple="False">
     <param name="infile1" type="data" format="tabular" label="@LABEL1@"/>
+    <param name="header1" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
     <param name="col1" multiple="@MULTIPLE1@" type="data_column" data_ref="infile1" label="Select the target column:"/>
     <param name="infile2" type="data" format="tabular" label="@LABEL2@"/>
+    <param name="header2" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
     <param name="col2" multiple="@MULTIPLE@" type="data_column" data_ref="infile2" label="Select target column(s):"/>
   </xml>
 
@@ -835,6 +837,21 @@
     </conditional>
   </xml>
 
+  <xml name="model_validation_common_options">
+    <param argument="cv" type="integer" value="" optional="true" label="cv" help="The number of folds in a (Stratified)KFold" />
+    <expand macro="n_jobs"/>
+    <expand macro="verbose"/>
+    <yield/>
+  </xml>
+
+  <xml name="scoring">
+    <param argument="scoring" type="text" value="" optional="true" label="scoring" help="A metric used to evaluate the estimator"/>
+  </xml>
+
+  <xml name="pre_dispatch">
+    <param argument="pre_dispatch" type="text" value="all" optional="true" label="pre_dispatch" help="Number of predispatched jobs for parallel execution"/>
+  </xml>
+
   <!-- Outputs -->
 
   <xml name="output">
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/mv_result01.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mv_result01.tabular Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,3 @@
+0.9452947345848994
+0.9926363525448115
+-0.4384003222944141
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/mv_result02.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mv_result02.tabular Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,10 @@
+1.6957921248350636
+-0.9248588846061156
+-0.48640795813792376
+0.647707440306449
+0.32740690920811427
+-0.8229559569886034
+1.2150108977866847
+0.14723254190255275
+0.6053186541119763
+0.3972102859168325
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/mv_result03.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mv_result03.tabular Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,3 @@
+0.9452947345848994
+0.9926363525448115
+-0.4384003222944141
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/mv_result04.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mv_result04.tabular Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,5 @@
+17
+56
+95
+134
+174
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/mv_result05.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mv_result05.tabular Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,1 @@
+0.4998435882784322
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/mv_result06.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mv_result06.tabular Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,5 @@
+0.07547169811320754 0.10344827586206896 0.10294117647058823
+0.07547169811320754 0.10344827586206896 0.10294117647058823
+0.07547169811320754 0.10344827586206896 0.10294117647058823
+0.07547169811320754 0.10344827586206896 0.10294117647058823
+0.07547169811320754 0.10344827586206896 0.10294117647058823
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/regression_metrics_result01
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/regression_metrics_result01 Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,2 @@
+explained_variance_score : 
+0.8260
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/regression_metrics_result02
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/regression_metrics_result02 Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,2 @@
+mean_absolute_error : 
+3.8706
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/regression_metrics_result03
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/regression_metrics_result03 Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,2 @@
+mean_squared_error : 
+26.0153
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/regression_metrics_result04
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/regression_metrics_result04 Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,2 @@
+mean_squared_log_error : 
+0.0061
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/regression_metrics_result05
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/regression_metrics_result05 Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,2 @@
+median_absolute_error : 
+3.0090
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/regression_metrics_result06
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/regression_metrics_result06 Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,2 @@
+r2_score : 
+0.8129
b
diff -r 961e9696f3d8 -r 82f51b60c4ee test-data/regression_test_y.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/regression_test_y.tabular Sat Apr 28 18:09:19 2018 -0400
b
@@ -0,0 +1,88 @@
+actual prediction
+66 69.857
+61 61.319
+52 51.891
+66 61.321
+70 66.463
+82 70.162
+85 78.848
+84 75.786
+65 62.121
+92 74.078
+61 63.647
+85 72.176
+44 38.458
+65 62.433
+69 71.594
+62 56.013
+64 60.943
+56 56.995
+53 56.748
+79 76.113
+63 63.758
+57 54.401
+67 66.493
+62 62.465
+59 58.786
+56 53.032
+65 66.769
+52 46.448
+66 62.122
+76 80.176
+64 73.833
+61 64.313
+48 55.188
+81 81.972
+77 74.178
+57 61.695
+58 53.636
+47 51.424
+68 68.929
+51 42.452
+77 70.385
+56 57.373
+73 76.172
+51 42.396
+59 61.098
+87 74.08
+58 52.745
+81 81.381
+58 53.324
+42 42.471
+49 46.507
+40 42.106
+65 64.17
+64 65.703
+70 74.13
+65 61.339
+53 55.177
+57 59.945
+53 54.651
+60 59.664
+67 65.474
+49 50.061
+53 60.849
+69 70.188
+55 60.062
+68 59.236
+76 71.868
+69 69.796
+78 76.83
+36 41.32
+74 76.868
+57 56.783
+69 60.378
+50 50.468
+56 54.426
+67 63.991
+48 43.711
+80 74.354
+48 47.306
+49 52.326
+57 53.526
+77 68.21
+81 73.607
+67 72.658
+66 63.243
+57 57.126
+45 46.04