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Load is_scaled in from zarr Template representation #2852

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Merged
h-mayorquin merged 4 commits into from
May 17, 2024
Merged

Load is_scaled in from zarr Template representation #2852

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6684978
load is_scaled in zarr representation
h-mayorquin May 15, 2024
8054df8
optional template
h-mayorquin May 15, 2024
43b4ee3
Update src/spikeinterface/core/template.py
h-mayorquin May 15, 2024
b52f599
indendation error
h-mayorquin May 15, 2024
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4 changes: 4 additions & 0 deletions src/spikeinterface/core/template.py
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Original file line number Diff line number Diff line change
Expand Up @@ -300,6 +300,9 @@ def from_zarr_group(cls, zarr_group: "zarr.Group") -> "Templates":
sampling_frequency = zarr_group.attrs["sampling_frequency"]
nbefore = zarr_group.attrs["nbefore"]

# TODO: Consider eliminating the True and make it required
is_scaled = zarr_group.attrs.get("is_scaled", True)

sparsity_mask = None
if "sparsity_mask" in zarr_group:
sparsity_mask = zarr_group["sparsity_mask"]
Expand All @@ -316,6 +319,7 @@ def from_zarr_group(cls, zarr_group: "zarr.Group") -> "Templates":
channel_ids=channel_ids,
unit_ids=unit_ids,
probe=probe,
is_scaled=is_scaled,
)

@staticmethod
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30 changes: 20 additions & 10 deletions src/spikeinterface/core/tests/test_template_class.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
from probeinterface import generate_multi_columns_probe


def generate_test_template(template_type):
def generate_test_template(template_type, is_scaled=True) -> Templates:
num_units = 2
num_samples = 5
num_channels = 3
Expand All @@ -21,7 +21,11 @@ def generate_test_template(template_type):

if template_type == "dense":
return Templates(
templates_array=templates_array, sampling_frequency=sampling_frequency, nbefore=nbefore, probe=probe
templates_array=templates_array,
sampling_frequency=sampling_frequency,
nbefore=nbefore,
probe=probe,
is_scaled=is_scaled,
)
elif template_type == "sparse": # sparse with sparse templates
sparsity_mask = np.array([[True, False, True], [False, True, False]])
Expand All @@ -42,6 +46,7 @@ def generate_test_template(template_type):
sampling_frequency=sampling_frequency,
nbefore=nbefore,
probe=probe,
is_scaled=is_scaled,
)

elif template_type == "sparse_with_dense_templates": # sparse with dense templates
Expand All @@ -53,12 +58,14 @@ def generate_test_template(template_type):
sampling_frequency=sampling_frequency,
nbefore=nbefore,
probe=probe,
is_scaled=is_scaled,
)


@pytest.mark.parametrize("is_scaled", [True, False])
@pytest.mark.parametrize("template_type", ["dense", "sparse"])
def test_pickle_serialization(template_type, tmp_path):
template = generate_test_template(template_type)
def test_pickle_serialization(template_type, is_scaled, tmp_path):
template = generate_test_template(template_type, is_scaled)

# Dump to pickle
pkl_path = tmp_path / "templates.pkl"
Expand All @@ -72,19 +79,21 @@ def test_pickle_serialization(template_type, tmp_path):
assert template == template_reloaded


@pytest.mark.parametrize("is_scaled", [True, False])
@pytest.mark.parametrize("template_type", ["dense", "sparse"])
def test_json_serialization(template_type):
template = generate_test_template(template_type)
def test_json_serialization(template_type, is_scaled):
template = generate_test_template(template_type, is_scaled)

json_str = template.to_json()
template_reloaded_from_json = Templates.from_json(json_str)

assert template == template_reloaded_from_json


@pytest.mark.parametrize("is_scaled", [True, False])
@pytest.mark.parametrize("template_type", ["dense", "sparse"])
def test_get_dense_templates(template_type):
template = generate_test_template(template_type)
def test_get_dense_templates(template_type, is_scaled):
template = generate_test_template(template_type, is_scaled)
dense_templates = template.get_dense_templates()
assert dense_templates.shape == (template.num_units, template.num_samples, template.num_channels)

Expand All @@ -94,9 +103,10 @@ def test_initialization_fail_with_dense_templates():
template = generate_test_template(template_type="sparse_with_dense_templates")


@pytest.mark.parametrize("is_scaled", [True, False])
@pytest.mark.parametrize("template_type", ["dense", "sparse"])
def test_save_and_load_zarr(template_type, tmp_path):
original_template = generate_test_template(template_type)
def test_save_and_load_zarr(template_type, is_scaled, tmp_path):
original_template = generate_test_template(template_type, is_scaled)

zarr_path = tmp_path / "templates.zarr"
original_template.to_zarr(str(zarr_path))
Expand Down