Fixed an issue preventing the splitter copy

Author: bowni

mplc/doc/documentation.md

@@ -252,7 +252,7 @@ There are 2 ways to select a dataset. You can either choose a pre-implemented da
                        from clusters they all share data samples from
           - `'specific'`: each partner with option `'specific'` receives data samples picked 
                          from cluster(s) it is the only one to receive from  
-    Example: `samples_split_option='advanced', samples_split_configuration=[[7, 'shared'], [6, 'shared'], [2, 'specific'], [1, 'specific']]]`
+    Example: `samples_split_option='advanced', samples_split_configuration=[[7, 'shared'], [6, 'shared'], [2, 'specific'], [1, 'specific']]`
 
     - `FlexibleSplitter`: in other cases one might want to specify in detail the split among partners (partner per partner and class per class). For that the `FlexibleSplitter` can be used. It is configured by indicating, for each partner in sequence, a list of the percentage of samples for each class: `[[% for class 1, ..., % for class n]]`. As above, it can be instantiated separately and then passed to the `Scenario` instance. Or the string identifier `'flexible'` can be used for the parameter `samples_split_option`, coupled with the split configuration passed to the keyword argument `samples_split_configuration`. String identified: `'flexible'`. 
     Example: `samples_split_option='flexible', samples_split_configuration=[[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5, 1.0, 1.0, 1.0, 0.5, 0.5, 0.5, 0.0]]` (this corresponds to 50% of the last 3 classes for partner 1, and 50% or 100% of each of the first 9 classes for partner 2).  

mplc/splitter.py

@@ -106,6 +106,7 @@ def __init__(self, amounts_per_partner, configuration, **kwargs):
                     "per partner from the samples_split_configuration provided.")
 
         # First we re-assemble the split configuration per cluster
+        self.configuration = configuration
         self.split_configuration = configuration
         self.samples_split_grouped_by_cluster = list(zip(*configuration))
 
@@ -204,6 +205,7 @@ class AdvancedSplitter(Splitter):
     name = 'Advanced Splitter'
 
     def __init__(self, amounts_per_partner, configuration, **kwargs):
+        self.configuration = configuration
         self.num_clusters, self.specific_shared = list(zip(*configuration))
         super().__init__(amounts_per_partner, **kwargs)