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Fix CI ValueError on NumPy 2.x by avoiding VLENUTF8 string dtype in tests #853

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Fix CI ValueError on NumPy 2.x by avoiding VLENUTF8 string dtype in tests #853

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tests: avoid NumPy 2.x boolean ambiguity by using fixed-length Unicod…
adilraza99 Feb 1, 2026
1d6c890
style: apply pre-commit formatting fixes
adilraza99 Feb 1, 2026
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20 changes: 10 additions & 10 deletions tests/anoph/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -620,7 +620,7 @@ def simulate_cnv_hmm(zarr_path, metadata_path, contigs, contig_sizes):
# Create samples array.
df_samples = pd.read_csv(metadata_path)
samples = df_samples["sample_id"].values
root.create_dataset(name="samples", data=samples, dtype=str)
root.create_dataset(name="samples", data=samples, dtype="U")

# Get the number of samples.
n_samples = len(df_samples)
Expand Down Expand Up @@ -669,7 +669,7 @@ def simulate_cnv_hmm(zarr_path, metadata_path, contigs, contig_sizes):
calldata_grp.create_dataset(name="RawCov", data=rawCov)

# Create the samples dataset (again) for this contig.
contig_grp.create_dataset(name="samples", data=samples, dtype=str)
contig_grp.create_dataset(name="samples", data=samples, dtype="U")

# Create variants group for this contig.
variants_grp = contig_grp.require_group("variants")
Expand Down Expand Up @@ -720,7 +720,7 @@ def simulate_cnv_coverage_calls(zarr_path, metadata_path, contigs, contig_sizes)
df_samples = pd.read_csv(metadata_path)
n_samples = len(df_samples)
samples = df_samples["sample_id"].values
root.create_dataset(name="samples", data=samples, dtype=str)
root.create_dataset(name="samples", data=samples, dtype="U")

for contig in contigs:
# Create the contig group.
Expand Down Expand Up @@ -766,7 +766,7 @@ def simulate_cnv_coverage_calls(zarr_path, metadata_path, contigs, contig_sizes)
calldata.create_dataset(name="GT", data=gt)

# Create the samples dataset (again) for this contig.
contig_grp.create_dataset(name="samples", data=samples, dtype=str)
contig_grp.create_dataset(name="samples", data=samples, dtype="U")

# Create the variants group for this contig.
variants_grp = contig_grp.require_group("variants")
Expand Down Expand Up @@ -839,7 +839,7 @@ def simulate_cnv_discordant_read_calls(zarr_path, metadata_path, contigs, contig
# Create samples array.
df_samples = pd.read_csv(metadata_path)
samples = df_samples["sample_id"].values
root.create_dataset(name="samples", data=samples, dtype=str)
root.create_dataset(name="samples", data=samples, dtype="U")

# Get the number of samples.
n_samples = len(df_samples)
Expand Down Expand Up @@ -909,7 +909,7 @@ def simulate_cnv_discordant_read_calls(zarr_path, metadata_path, contigs, contig
calldata_grp.create_dataset(name="GT", data=gt)

# Create the samples dataset (again) for this contig.
contig_grp.create_dataset(name="samples", data=samples, dtype=str)
contig_grp.create_dataset(name="samples", data=samples, dtype="U")

# Create the variants group for this contig.
variants_grp = contig_grp.require_group("variants")
Expand Down Expand Up @@ -1589,7 +1589,7 @@ def init_haplotypes(self):
/ "zarr"
)
root = zarr.open(zarr_path, mode="w")
root.create_dataset(name="samples", data=samples, dtype=str)
root.create_dataset(name="samples", data=samples, dtype="U")
for contig in self.contigs:
n_sites = self.n_hap_sites[analysis][contig]
gt = np.random.choice(
Expand Down Expand Up @@ -1620,7 +1620,7 @@ def init_haplotypes(self):
/ "zarr"
)
root = zarr.open(zarr_path, mode="w")
root.create_dataset(name="samples", data=samples, dtype=str)
root.create_dataset(name="samples", data=samples, dtype="U")
for contig in self.contigs:
n_sites = self.n_hap_sites[analysis][contig]
gt = np.random.choice(
Expand Down Expand Up @@ -1651,7 +1651,7 @@ def init_haplotypes(self):
/ "zarr"
)
root = zarr.open(zarr_path, mode="w")
root.create_dataset(name="samples", data=samples, dtype=str)
root.create_dataset(name="samples", data=samples, dtype="U")
for contig in self.contigs:
n_sites = self.n_hap_sites[analysis][contig]
gt = np.random.choice(
Expand Down Expand Up @@ -2300,7 +2300,7 @@ def init_haplotypes(self):
/ "zarr"
)
root = zarr.open(zarr_path, mode="w")
root.create_dataset(name="samples", data=samples, dtype=str)
root.create_dataset(name="samples", data=samples, dtype="U")
for contig in self.contigs:
n_sites = self.n_hap_sites[analysis][contig]
gt = np.random.choice(
Expand Down
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