# HG changeset patch
# User Frederic Bastien <bastienf@iro.umontreal.ca>
# Date 1209487031 14400
# Node ID c5b07e87b0cbec055c7952689a77eb833e91a234
# Parent  a5c70dc42972de2691a649c1e370eb9bf115dc25
comments  modif made by Yoshua

diff -r a5c70dc42972 -r c5b07e87b0cb dataset.py
--- a/dataset.py	Tue Apr 29 11:25:36 2008 -0400
+++ b/dataset.py	Tue Apr 29 12:37:11 2008 -0400
@@ -33,6 +33,8 @@
     * for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N):
     * for mini1,mini2,mini3 in dataset.minibatches([field1, field2, ...],minibatch_size=N):
     * for example in dataset:
+        print example['x']
+    * for x,y,z in dataset:
     Each of these is documented below. All of these iterators are expected
     to provide, in addition to the usual 'next()' method, a 'next_index()' method
     which returns a non-negative integer pointing to the position of the next
@@ -43,7 +45,8 @@
     dataset length.
     
     To iterate over fields, one can do
-    * for fields in dataset.fields()
+    * for field in dataset.fields():
+         for field_value in field: # iterate over the values associated to that field for all the dataset examples
     * for fields in dataset(field1,field2,...).fields() to select a subset of fields
     * for fields in dataset.fields(field1,field2,...) to select a subset of fields
     and each of these fields is iterable over the examples:
@@ -63,7 +66,8 @@
 
     Note: The content of a field can be of any type. Field values can also be 'missing'
     (e.g. to handle semi-supervised learning), and in the case of numeric (numpy array)
-    fields (i.e. an ArrayFieldsDataSet), NaN plays the role of a missing value.
+    fields (i.e. an ArrayFieldsDataSet), NaN plays the role of a missing value. 
+    What about non-numeric values? None.
 
     Dataset elements can be indexed and sub-datasets (with a subset
     of examples) can be extracted. These operations are not supported
@@ -101,7 +105,7 @@
     works if they all have the same fields.
 
     According to the same logic, and viewing a DataSetFields object associated to
-    a DataSet as a kind of transpose of it, fields1 + fields2 concatenates fields of
+    a DataSet as a kind of transpose of it, fields1 & fields2 concatenates fields of
     a DataSetFields fields1 and fields2, and fields1 | fields2 concatenates their
     examples.