Fix numpy warnings

Author: benjeffery

python/tests/test_highlevel.py

@@ -1238,7 +1238,7 @@ def test_samples_time_interval(self, time_interval):
 
     def test_samples_example(self):
         tables = tskit.TableCollection(sequence_length=10)
-        time = [np.array(0), 0, np.array([1]), 1, 1, 3, 3.00001, 3.0 - 0.0001, 1 / 3]
+        time = [0, 0, 1, 1, 1, 3, 3.00001, 3.0 - 0.0001, 1 / 3]
         pops = [1, 3, 1, 2, 1, 1, 1, 3, 1]
         for _ in range(max(pops) + 1):
             tables.populations.add_row()

python/tests/test_tables.py

@@ -813,7 +813,11 @@ def test_bad_offsets(self):
 
             for _list_col, offset_col in self.ragged_list_columns:
                 original_offset = np.copy(input_data[offset_col.name])
-                input_data[offset_col.name][0] = -1
+                # As numpy no longer allows conversion of out-of-bounds values, we
+                # explictly cast first.
+                input_data[offset_col.name][0] = np.array(-1).astype(
+                    input_data[offset_col.name].dtype
+                )
                 with pytest.raises(ValueError):
                     t.set_columns(**input_data)
                 input_data[offset_col.name] = np.copy(original_offset)
@@ -828,7 +832,9 @@ def test_bad_offsets(self):
                     t.set_columns(**input_data)
                 input_data[offset_col.name] = np.copy(original_offset)
 
-                input_data[offset_col.name][0] = -1
+                input_data[offset_col.name][0] = np.array(-1).astype(
+                    input_data[offset_col.name].dtype
+                )
                 with pytest.raises(ValueError):
                     t.append_columns(**input_data)
                 input_data[offset_col.name] = np.copy(original_offset)

python/tskit/formats.py

@@ -1,6 +1,6 @@
 # MIT License
 #
-# Copyright (c) 2018-2021 Tskit Developers
+# Copyright (c) 2018-2023 Tskit Developers
 # Copyright (c) 2016-2017 University of Oxford
 #
 # Permission is hereby granted, free of charge, to any person obtaining a copy
@@ -471,6 +471,10 @@ def _dump_legacy_hdf5_v10(tree_sequence, root):
 def _load_legacy_hdf5_v10(root, remove_duplicate_positions=False):
     # We cannot have duplicate positions in v10, so this parameter is ignored
     sequence_length = root.attrs["sequence_length"]
+    try:
+        sequence_length = sequence_length[0]
+    except TypeError:
+        pass
     tables = tskit.TableCollection(sequence_length)
 
     nodes_group = root["nodes"]

python/tskit/trees.py

@@ -8572,7 +8572,7 @@ def fst_func(sample_set_sizes, flattened, indexes, **kwargs):
                 divergences.shape = (divergences.shape[0], 1, divergences.shape[1])
                 diversities.shape = (diversities.shape[0], 1, diversities.shape[1])
 
-            fst = np.repeat(1.0, np.product(divergences.shape))
+            fst = np.repeat(1.0, np.prod(divergences.shape))
             fst.shape = divergences.shape
             for i, (u, v) in enumerate(indexes):
                 denom = (
@@ -9167,7 +9167,7 @@ def pairwise_diversity(self, samples=None):
         return float(
             self.diversity(
                 [samples], windows=[0, self.sequence_length], span_normalise=False
-            )[0]
+            )[0][0]
         )
 
     def get_time(self, u):