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Add stable unit filter and load_spikes tests #61

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Merged
merged 5 commits into from
Mar 30, 2025
Merged

Add stable unit filter and load_spikes tests #61

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1ff091b
add load_spikes test
ryanharvey1 Mar 28, 2025
3c31458
add filter for stable
ryanharvey1 Mar 28, 2025
10c43c6
trying pytest.fixture
ryanharvey1 Mar 29, 2025
c8a0e4c
save and load test data
ryanharvey1 Mar 29, 2025
3fcf12f
remove unneeded import
ryanharvey1 Mar 30, 2025
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27 changes: 22 additions & 5 deletions neuro_py/io/loading.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
from joblib import Parallel, delayed
from scipy import signal

import neuro_py as npy
from neuro_py.behavior.kinematics import get_speed
from neuro_py.process.intervals import find_interval, in_intervals
from neuro_py.process.peri_event import get_participation
Expand Down Expand Up @@ -1851,6 +1852,8 @@ def load_spikes(
other_metric: Union[str, None] = None,
other_metric_value: Union[str, None] = None,
support: Union[nel.EpochArray, None] = None,
remove_unstable: bool = False,
stable_interval_width: int = 600,
) -> Tuple[Union[nel.SpikeTrainArray, None], Union[pd.DataFrame, None]]:
"""
Load specific cells' spike times.
Expand All @@ -1873,6 +1876,10 @@ def load_spikes(
Value of the metric to restrict spikes to, by default None.
support : Union[nel.EpochArray, None], optional
Time support to provide, by default None.
remove_unstable : bool, optional
If True, remove unstable cells, by default False.
stable_interval_width : int, optional
Width of the stable interval in seconds, by default 600.

Returns
-------
Expand All @@ -1884,11 +1891,8 @@ def load_spikes(
if not isinstance(brainRegion, list):
brainRegion = [brainRegion]

# get sample rate from xml or session
try:
_, _, fs_dat, _ = loadXML(basepath)
except Exception:
fs_dat = load_extracellular_metadata(basepath).get("sr", None)
# get sample rate from session
fs_dat = load_extracellular_metadata(basepath).get("sr", None)

if fs_dat is None:
return None, None
Expand Down Expand Up @@ -1949,6 +1953,19 @@ def load_spikes(
cell_metrics = cell_metrics[restrict_idx]
st = st[restrict_idx]

if remove_unstable and len(st) > 0:
starts = np.arange(
np.hstack(st).min(),
np.hstack(st).max() - stable_interval_width,
stable_interval_width,
)
stops = starts + stable_interval_width

bst = npy.process.count_in_interval(st, starts, stops, "counts")
restrict_idx = np.sum(bst == 0, axis=1) < 2 # allow for 1 unstable interval max
cell_metrics = cell_metrics[restrict_idx]
st = st[restrict_idx]

# get spike train array
try:
if support is not None:
Expand Down
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