MRG: update to code for forthcoming sourmash release

Cargo.toml

@@ -12,7 +12,8 @@ crate-type = ["cdylib"]
 pyo3 = { version = "0.22.3", features = ["extension-module", "anyhow"] }
 rayon = "1.10.0"
 serde = { version = "1.0.210", features = ["derive"] }
-sourmash = { version = "0.15.2", features = ["branchwater"] }
+#sourmash = { version = "0.15.2", features = ["branchwater"] }
+sourmash = { git = "https://github.com/sourmash-bio/sourmash.git", branch = "refactor_rs_downsample", features = ["branchwater"] }
 serde_json = "1.0.128"
 niffler = "2.4.0"
 log = "0.4.22"

src/manysearch.rs

@@ -219,6 +219,7 @@ fn downsample_and_inflate_abundances(
     // avoid downsampling if we can
     if against_scaled != query_scaled {
         let against_ds = against
+            .clone()
             .downsample_scaled(query.scaled())
             .expect("cannot downsample sketch");
         (abunds, sum_weighted) = query.inflated_abundances(&against_ds)?;

src/python/tests/test_fastmultigather.py

@@ -959,15 +959,15 @@ def test_indexed_full_output(runtmp):
     # check a few columns
     average_ani = set(df['average_containment_ani'])
     avg_ani = set([round(x, 4) for x in average_ani])
-    assert avg_ani == {0.8502, 0.8584, 0.8602}
+    assert avg_ani == {0.9221, 0.9306, 0.9316} # @CTB check against py gather
 
     f_unique_weighted = set(df['f_unique_weighted'])
     f_unique_weighted = set([round(x, 4) for x in f_unique_weighted])
     assert f_unique_weighted == {0.0063, 0.002, 0.0062}
 
     unique_intersect_bp = set(df['unique_intersect_bp'])
     unique_intersect_bp = set([round(x,4) for x in unique_intersect_bp])
-    assert unique_intersect_bp == {44000, 18000, 22000}
+    assert unique_intersect_bp == {4400000, 1800000, 2200000}
 
 
 def test_nonindexed_full_vs_sourmash_gather(runtmp):

src/utils.rs

@@ -478,7 +478,10 @@ pub fn load_sketches_above_threshold(
             if let Ok(against_sig) = against_collection.sig_from_record(against_record) {
                 if let Some(against_mh) = against_sig.minhash() {
                     // downsample against_mh, but keep original md5sum
-                    let against_mh_ds = against_mh.downsample_scaled(query.scaled()).unwrap();
+                    let against_mh_ds = against_mh
+                        .clone()
+                        .downsample_scaled(query.scaled())
+                        .unwrap();
                     if let Ok(overlap) = against_mh_ds.count_common(query, false) {
                         if overlap >= threshold_hashes {
                             let result = PrefetchResult {