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Update tests to use in_construct_mode=True for invalid timeseries #556

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Jan 28, 2025
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Update tests to use in_construct_mode=True for invalid timeseries #556

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2 changes: 2 additions & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,8 @@

## Improvements
* Added a section for describing the issues with negative timestamps in `TimeSeries` [#545](https://github.com/NeurodataWithoutBorders/nwbinspector/pull/545)
* Use alternate way of generating `TimeSeries` objects to avoid new pynwb error when the shape of the first dimension of
data does not match the length of timestamps [#556](https://github.com/NeurodataWithoutBorders/nwbinspector/pull/556)

# v0.6.1

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4 changes: 3 additions & 1 deletion tests/test_inspector.py
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Expand Up @@ -95,7 +95,9 @@ def add_flipped_data_orientation_to_processing(nwbfile: NWBFile):
def add_non_matching_timestamps_dimension(nwbfile: NWBFile):
timestamps = [1.0, 2.1, 3.0]
timestamps_length = len(timestamps)
time_series = TimeSeries(
# Use __new__ and in_construct_mode=True to bypass the check in pynwb for data.shape[0] == len(timestamps)
time_series = TimeSeries.__new__(TimeSeries, in_construct_mode=True)
time_series.__init__(
name="test_time_series_3",
data=np.zeros(shape=(timestamps_length + 1, timestamps_length)),
timestamps=timestamps,
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50 changes: 33 additions & 17 deletions tests/unit_tests/test_time_series.py
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Expand Up @@ -124,17 +124,20 @@ def test_check_timestamps_match_first_dimension_special_skip(tmp_path):
image_height = 15
num_channels = 3
dtype = "uint8"
image_series = pynwb.image.ImageSeries(

# Use __new__ and in_construct_mode=True to bypass the check in pynwb for data.shape[0] == len(timestamps)
image_series = pynwb.image.ImageSeries.__new__(pynwb.image.ImageSeries, in_construct_mode=True)
image_series.__init__(
name="ImageSeries",
unit="n.a.",
unit="N/A",
data=np.empty(shape=(num_images, image_width, image_height, num_channels), dtype=dtype),
timestamps=[],
)
nwbfile.add_acquisition(image_series)
nwbfile.add_acquisition(
pynwb.image.IndexSeries(
name="IndexSeries",
unit="n.a.",
unit="N/A",
data=[0, 1],
indexed_timeseries=image_series,
timestamps=[0.5, 0.6],
Expand All @@ -152,14 +155,15 @@ def test_check_timestamps_match_first_dimension_special_skip(tmp_path):


def test_check_timestamps_match_first_dimension_bad():
assert check_timestamps_match_first_dimension(
time_series=pynwb.TimeSeries(
name="test_time_series",
unit="test_units",
data=np.empty(shape=4),
timestamps=[1.0, 2.0, 3.0],
)
) == InspectorMessage(
# Use __new__ and in_construct_mode=True to bypass the check in pynwb for data.shape[0] == len(timestamps)
time_series = pynwb.TimeSeries.__new__(pynwb.TimeSeries, in_construct_mode=True)
time_series.__init__(
name="test_time_series",
unit="test_units",
data=np.empty(shape=4),
timestamps=[1.0, 2.0, 3.0],
)
assert check_timestamps_match_first_dimension(time_series=time_series) == InspectorMessage(
message="The length of the first dimension of data (4) does not match the length of timestamps (3).",
importance=Importance.CRITICAL,
check_function_name="check_timestamps_match_first_dimension",
Expand All @@ -170,9 +174,15 @@ def test_check_timestamps_match_first_dimension_bad():


def test_check_timestamps_empty_data():
assert check_timestamps_match_first_dimension(
time_series=pynwb.TimeSeries(name="test_time_series", unit="test_units", data=[], timestamps=[1.0, 2.0, 3.0])
) == InspectorMessage(
# Use __new__ and in_construct_mode=True to bypass the check in pynwb for data.shape[0] == len(timestamps)
time_series = pynwb.TimeSeries.__new__(pynwb.TimeSeries, in_construct_mode=True)
time_series.__init__(
name="test_time_series",
unit="test_units",
data=[],
timestamps=[1.0, 2.0, 3.0],
)
assert check_timestamps_match_first_dimension(time_series=time_series) == InspectorMessage(
message="The length of the first dimension of data (0) does not match the length of timestamps (3).",
importance=Importance.CRITICAL,
check_function_name="check_timestamps_match_first_dimension",
Expand All @@ -183,9 +193,15 @@ def test_check_timestamps_empty_data():


def test_check_timestamps_empty_timestamps():
assert check_timestamps_match_first_dimension(
time_series=pynwb.TimeSeries(name="test_time_series", unit="test_units", data=np.empty(shape=4), timestamps=[])
) == InspectorMessage(
# Use __new__ and in_construct_mode=True to bypass the check in pynwb for data.shape[0] == len(timestamps)
time_series = pynwb.TimeSeries.__new__(pynwb.TimeSeries, in_construct_mode=True)
time_series.__init__(
name="test_time_series",
unit="test_units",
data=np.empty(shape=4),
timestamps=[],
)
assert check_timestamps_match_first_dimension(time_series=time_series) == InspectorMessage(
message="The length of the first dimension of data (4) does not match the length of timestamps (0).",
importance=Importance.CRITICAL,
check_function_name="check_timestamps_match_first_dimension",
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