GA: add 'intersection' method (closes #340)

skgenome/gary.py

@@ -11,7 +11,7 @@
 import pandas as pd
 
 from .chromsort import sorter_chrom
-from .intersect import by_ranges, into_ranges, iter_ranges, iter_slices
+from .intersect import by_ranges, into_ranges, iter_ranges, iter_slices, _monotonic
 from .merge import flatten, merge
 from .rangelabel import to_label
 from .subtract import subtract
@@ -617,6 +617,23 @@ def flatten(self, combine=None, split_columns=None):
         return self.as_dataframe(flatten(self.data, combine=combine,
                                          split_columns=split_columns))
 
+    def intersection(self, other, mode='outer'):
+        """Select the bins in `self` that overlap the regions in `other`.
+
+        The extra fields of `self`, but not `other`, are retained in the output.
+        """
+        # TODO options for which extra fields to keep
+        #   by default, keep just the fields in 'table'
+        if mode == 'trim':
+            # Slower
+            chunks = [chunk.data for _, chunk in
+                      self.by_ranges(other, mode=mode, keep_empty=False)]
+            return self.as_dataframe(pd.concat(chunks))
+        else:
+            slices = iter_slices(self.data, other.data, mode, False)
+            indices = np.concatenate([self.data.index[slc] for slc in slices])
+            return self.as_dataframe(self.data.iloc[indices])
+
     def merge(self, bp=0, stranded=False, combine=None):
         """Merge adjacent or overlapping regions into single rows.
 

test/test_genome.py

@@ -453,10 +453,15 @@ def test_intersect(self):
             (self.regions_2, selections2, expectations2),
         ):
             for mode in ('outer', 'trim', 'inner'):
+                # Iterative intersection
                 grouped_results = regions.by_ranges(selections, mode=mode)
                 for (_coord, result), expect in zip(grouped_results,
                                                     expectations[mode]):
                     self._compare_regions(result, self._from_intervals(expect))
+                # Single-object intersect
+                result = regions.intersection(selections, mode=mode)
+                expect = self._from_intervals(sum(expectations[mode], []))
+                self._compare_regions(result, expect)
 
     def test_subtract(self):
         # Test cases: