added relevant documentation

Author: janvanrijn

openml/evaluations/evaluation.py

@@ -1,6 +1,28 @@
 
 class OpenMLEvaluation(object):
+    '''
+    Contains all meta-information about a run / evaluation combination,
+    according to the evaluation/list function
 
+    Parameters
+       ----------
+        run_id : int
+        task_id : int
+        setup_id : int
+        flow_id : int
+        flow_name : str
+        data_id : int
+        data_name : str
+            the name of the dataset
+        function : str
+            the evaluation function of this item (e.g., accuracy)
+        upload_time : str
+            the time of evaluation
+        value : float
+            the value of this evaluation
+        array_data : str
+            list of information per class (e.g., in case of precision, auroc, recall)
+    '''
     def __init__(self, run_id, task_id, setup_id, flow_id, flow_name,
                  data_id, data_name, function, upload_time, value,
                  array_data=None):

openml/study/functions.py

@@ -13,6 +13,11 @@ def _multitag_to_list(result_dict, tag):
 
 
 def get_study(study_id):
+    '''
+    Retrieves all relevant information of an OpenML study from the server
+    Note that some of the (data, tasks, flows, setups) fields can be empty
+    (depending on information on the server)
+    '''
     xml_string = _perform_api_call("study/%d" %(study_id))
     result_dict = xmltodict.parse(xml_string)['oml:study']
     id = int(result_dict['oml:id'])

openml/study/study.py

@@ -1,5 +1,39 @@
 
 class OpenMLStudy(object):
+    '''
+    An OpenMLStudy represents the OpenML concept of a study. It contains
+    the following information: name, id, description, creation date,
+    creator id and a set of tags.
+
+    According to this list of tags, the study object receives a list of
+    OpenML object ids (datasets, flows, tasks and setups).
+
+    Can be used to obtain all relevant information from a study at once.
+
+    Parameters
+       ----------
+        id : int
+            the study id
+        name : str
+            the name of the study (meta-info)
+        description : str
+            brief description (meta-info)
+        creation_date : str
+            date of creation (meta-info)
+        creator : int
+            openml user id of the owner / creator
+        tag : list(dict)
+            The list of tags shows which tags are associated with the study.
+            Each tag is a dict of (tag) name, window_start and write_access.
+        data : list
+            a list of data ids associated with this study
+        tasks : list
+            a list of task ids associated with this study
+        flows : list
+            a list of flow ids associated with this study
+        setups : list
+            a list of setup ids associated with this study
+    '''
 
     def __init__(self, id, name, description, creation_date, creator,
                  tag, data, tasks, flows, setups):