fix: resolve NumPy 2.x boolean ambiguity in SNP frequency analysis

Replace built-in all() with .all() method on pandas Series in
_prep_samples_for_cohort_grouping() to avoid NumPy 2.x ValueError.

NumPy 2.x raises ValueError when attempting to evaluate the truth value
of an array/Series with more than one element in a boolean context.

Before:
  if not all(df_samples[period_by].apply(...)):

After:
  if not df_samples[period_by].apply(...).all():

The .all() method correctly reduces the Series to a single boolean value,
maintaining identical behavior with both NumPy 1.26.x and 2.x.

Fixes allele_frequencies_advanced test failures under NumPy 2.x.

Author: adilraza99

malariagen_data/anoph/frq_base.py

@@ -53,11 +53,9 @@ def _prep_samples_for_cohort_grouping(*, df_samples, area_by, period_by, taxon_b
             )
 
         # Raise a ValueError if the specified period_by column does not contain instances pd.Period.
-        if not all(
-            df_samples[period_by].apply(
-                lambda value: pd.isnull(value) or isinstance(value, pd.Period)
-            )
-        ):
+        if not df_samples[period_by].apply(
+            lambda value: pd.isnull(value) or isinstance(value, pd.Period)
+        ).all():
             raise TypeError(
                 f"Invalid values in {period_by!r} column. Must be either pandas.Period or null."
             )