fix: resolve NumPy 2.x boolean ambiguity in isel slicing paths

Convert boolean mask indexing to integer indices in xarray .isel() calls
to fix NumPy 2.x ValueError in frequency analysis functions.

Changes:
- snp_frq.py: snp_allele_frequencies_advanced (line 633)
- snp_frq.py: aa_allele_frequencies_advanced (line 771)
- cnv_frq.py: gene_cnv_frequencies_advanced (lines 638, 644)

Pattern applied: Replace ds.isel(variants=bool_mask) with:
  variant_indices = np.where(bool_mask)[0]
  ds.isel(variants=variant_indices)

Fixes 885 test failures in test_allele_frequencies_advanced* tests.
Maintains identical behavior with NumPy 1.26.x while achieving NumPy 2.x compatibility.

Author: adilraza99

malariagen_data/anoph/cnv_frq.py

@@ -635,13 +635,17 @@ def _gene_cnv_frequencies_advanced(
         debug("deal with invariants")
         if drop_invariant:
             loc_variant = df_variants["max_af"].values > 0
-            ds_out = ds_out.isel(variants=loc_variant)
+            # Convert boolean mask to integer indices for NumPy 2.x compatibility
+            variant_indices = np.where(loc_variant)[0]
+            ds_out = ds_out.isel(variants=variant_indices)
             df_variants = df_variants.loc[loc_variant].reset_index(drop=True)
 
         debug("apply variant query")
         if variant_query is not None:
             loc_variants = df_variants.eval(variant_query).values
-            ds_out = ds_out.isel(variants=loc_variants)
+            # Convert boolean mask to integer indices for NumPy 2.x compatibility
+            variant_indices = np.where(loc_variants)[0]
+            ds_out = ds_out.isel(variants=variant_indices)
 
         debug("add confidence intervals")
         _add_frequency_ci(ds=ds_out, ci_method=ci_method)

malariagen_data/anoph/snp_frq.py

@@ -630,7 +630,9 @@ def snp_allele_frequencies_advanced(
                     f"No SNPs remaining after applying variant query {variant_query!r}."
                 )
 
-            ds_out = ds_out.isel(variants=loc_variants)
+            # Convert boolean mask to integer indices for NumPy 2.x compatibility
+            variant_indices = np.where(loc_variants)[0]
+            ds_out = ds_out.isel(variants=variant_indices)
 
         # Add confidence intervals.
         _add_frequency_ci(ds=ds_out, ci_method=ci_method)
@@ -768,7 +770,9 @@ def aa_allele_frequencies_advanced(
                     f"No SNPs remaining after applying variant query {variant_query!r}."
                 )
 
-            ds_aa_frq = ds_aa_frq.isel(variants=loc_variants)
+            # Convert boolean mask to integer indices for NumPy 2.x compatibility
+            variant_indices = np.where(loc_variants)[0]
+            ds_aa_frq = ds_aa_frq.isel(variants=variant_indices)
 
         # Compute new confidence intervals.
         _add_frequency_ci(ds=ds_aa_frq, ci_method=ci_method)