Identify blocks that satisfy the criteria for being a learning block.

cml/domain/data_source.py

@@ -57,3 +57,22 @@ class Preprocessor:
 class LearnblockIdentifier:
     def __init__(self, settings):
         self.settings = settings
+        self.column_pairs = (("T", "Z"), ("T", "Sigma"), ("Sigma", "Z"))
+
+    def identify(self, block):
+        for pair in self.column_pairs:
+            for possible_learnblock in self._identify_relatives(block, *pair):
+                if self._is_learn_block(possible_learnblock.length):
+                    yield possible_learnblock
+
+    def _is_learn_block(self, block_length):
+        return block_length > self.settings.learn_block_minimum
+
+    def _identify_relatives(self, block, *args):
+        # TODO (dmt): Implement density and kmeans!
+        already_seen = set()
+        for value_pair in block.get_duplicated_pairs(args[0], args[1]):
+            if value_pair not in already_seen:
+                already_seen.add(value_pair)
+                kw = {args[0]: value_pair[0], args[1]: value_pair[1]}
+                yield block.get_values(**kw)