rolled back

src/oaklib/cli.py

@@ -2654,12 +2654,6 @@ def similarity_pair(terms, predicates, autolabel: bool, output: TextIO, output_t
     show_default=True,
     help="Score used for summarization",
 )
-@click.option(
-    "--quick/--no-quick",
-    default=False,
-    show_default=True,
-    help="If set, results will be generated by Rust.",
-)
 @autolabel_option
 @output_type_option
 @click.argument("terms", nargs=-1)
@@ -2669,7 +2663,6 @@ def similarity(
     set1_file,
     set2_file,
     autolabel: bool,
-    quick: bool,
     min_jaccard_similarity: Optional[float],
     min_ancestor_information_content: Optional[float],
     main_score_field,
@@ -2759,30 +2752,21 @@ def similarity(
             else:
                 set2it = query_terms_iterator(terms, impl)
         actual_predicates = _process_predicates_arg(predicates)
-        if quick:
-            impl.all_by_all_pairwise_similarity_quick(
-                set1it,
-                set2it,
-                predicates=actual_predicates,
-                min_jaccard_similarity=min_jaccard_similarity,
-                min_ancestor_information_content=min_ancestor_information_content,
-            )
-        else:
-            for sim in impl.all_by_all_pairwise_similarity(
-                set1it,
-                set2it,
-                predicates=actual_predicates,
-                min_jaccard_similarity=min_jaccard_similarity,
-                min_ancestor_information_content=min_ancestor_information_content,
-            ):
-                if autolabel:
-                    # TODO: this can be made more efficient
-                    sim.subject_label = impl.label(sim.subject_id)
-                    sim.object_label = impl.label(sim.object_id)
-                    sim.ancestor_label = impl.label(sim.ancestor_id)
-                writer.emit(sim)
-            writer.finish()
-            writer.file.close()
+        for sim in impl.all_by_all_pairwise_similarity(
+            set1it,
+            set2it,
+            predicates=actual_predicates,
+            min_jaccard_similarity=min_jaccard_similarity,
+            min_ancestor_information_content=min_ancestor_information_content,
+        ):
+            if autolabel:
+                # TODO: this can be made more efficient
+                sim.subject_label = impl.label(sim.subject_id)
+                sim.object_label = impl.label(sim.object_id)
+                sim.ancestor_label = impl.label(sim.ancestor_id)
+            writer.emit(sim)
+        writer.finish()
+        writer.file.close()
     else:
         raise NotImplementedError(f"Cannot execute this using {impl} of type {type(impl)}")
 

src/oaklib/implementations/semsimian/semsimian_implementation.py

@@ -165,30 +165,3 @@ def all_by_all_pairwise_similarity(
                     sim.jaccard_similarity = 0
                     sim.ancestor_information_content = 0
                 yield sim
-
-    def all_by_all_pairwise_similarity_quick(
-        self,
-        subjects: Iterable[CURIE],
-        objects: Iterable[CURIE],
-        predicates: List[PRED_CURIE] = None,
-        min_jaccard_similarity: Optional[float] = None,
-        min_ancestor_information_content: Optional[float] = None,
-    ) -> None:
-        """
-        Compute similarity for all combinations of terms in subsets vs all terms in objects
-
-        :param subjects:
-        :param objects:
-        :param predicates:
-        :return:
-        """
-        objects = list(objects)
-        logging.info(f"Calculating all-by-all pairwise similarity for {len(objects)} objects")
-        self.semsimian.all_by_all_pairwise_similarity_quick(
-            subject_terms=set(subjects),
-            object_terms=set(objects),
-            minimum_jaccard_threshold=min_jaccard_similarity,
-            minimum_resnik_threshold=min_ancestor_information_content,
-            predicates=set(predicates) if predicates else None,
-            outfile="rust_output.tsv",
-        )