Get overlapping data samples through joins.

cml/ports/source_adapters.py

@@ -63,6 +63,10 @@ class PandasBlock:
     def __len__(self):
         return self.__data_block.shape[0]
 
+    @property
+    def data_block(self):
+        return self.__data_block
+
     def has_nan(self):
         return self.__data_block.isna().any()[0]
 
@@ -188,6 +192,28 @@ class PandasBlock:
 
         self.__data_block.drop(remove_columns, axis=1, inplace=True)
 
+    def get_overlapping(self, block, on=None):
+        if len(block) < len(self):
+            biggest = block
+            block = self
+        else:
+            biggest = self
+            block = block
+
+        join = biggest.data_block.join(
+            block.data_block.set_index("T"),
+            on="T",
+            lsuffix="_other",
+            how="inner")
+
+        for column in join.columns:
+            if column not in ("T", "Z", "Z_other"):
+                join.drop(column, axis=1, inplace=True)
+        join = join[["Z", "Z_other", "T"]]
+        # TODO (dmt): Make purpose and origin a tuple.
+        print(len(join))
+        return PandasBlock(join, self.purpose, self.origin)
+
 
 class PandasAdapter:
     def __init__(self, data_frame):
@@ -199,7 +225,7 @@ class PandasAdapter:
         return block
 
     @classmethod
-    def read_csv_data(cls, path):
+    def read_csv(cls, path):
         data_frame = pd.read_csv(path, index_col=False)
         return PandasAdapter(data_frame)