dodal dva widgeta v orange paket

workflows/cforange/library.py

-import re
-
 def cforange_split_dataset(input_dict):
     import orange
     output_dict = {}
@@ -9,4 +7,4 @@ def cforange_split_dataset(input_dict):
     test_data = data.select(selection,1)
     output_dict['train_data']=train_data
     output_dict['test_data']=test_data
-    return output_dict
\ No newline at end of file
+    return output_dict

workflows/library.py

@@ -21,6 +21,39 @@ def add_multiple(input_dict):
         output_dict['sum'] = int(i)+output_dict['sum']
     return output_dict
 
+def cforange_score_estimation(input_dict):
+    import orange
+    import orngFSS
+    data = input_dict['dataset']
+    ma = orngFSS.attMeasure(data,orange.MeasureAttribute_relief(k=int(input_dict['k']), m=int(input_dict['m'])))
+    output_string = ""
+    output_dict = {}
+    output_dict['results'] = ma
+    return output_dict
+
+def cforange_best_natts(input_dict):
+    import orange
+    import orngFSS
+    data = input_dict['dataset']
+    scores = input_dict['scores']
+    n = int(input_dict['n'])
+    new_dataset = orngFSS.selectBestNAtts(data,scores,n)
+    output_dict={}
+    output_dict['new_dataset'] = new_dataset
+    return output_dict
+
+def cforange_atts_above_thresh(input_dict):
+    import orange
+    import orngFSS
+    data = input_dict['dataset']
+    scores = input_dict['scores']
+    thresh = float(input_dict['thresh'])
+    new_dataset = orngFSS.selectAttsAboveThresh(data,scores,thresh)
+    output_dict={}
+    output_dict['new_dataset'] = new_dataset
+    return output_dict
+
+
 def delay(input_dict,widget):
     widget.progress=0
     widget.save()