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minor fix for LF proc #484

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Jan 10, 2025
Merged

minor fix for LF proc #484

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18 changes: 10 additions & 8 deletions docs/recipes/low_freq_proc.qmd
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Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ cutoff_freq = 1 / (2*dt)
filter_safety_factor = 0.9

# Enter memory size to be dedicated for processing (in MB)
memory_limit_MB = 75
memory_limit_MB = 1_000

# Define a tolerance for determining edge effects (used in next step)
tolerance = 1e-3
Expand Down Expand Up @@ -69,13 +69,16 @@ memory_size_per_second_MB = memory_size_per_second / 1e6
chunk_size = memory_limit_MB / memory_size_per_second_MB

# Ensure `chunk_size` does not exceed the spool length
merged_sp = sp.chunk(time=None)[0]
if chunk_size > merged_sp.seconds:
time_step = sp[0].get_coord('time').step
time_min = sp[0].get_coord('time').min()
time_max = sp[-1].get_coord('time').max()
spool_length = dc.to_float((time_max - time_min + time_step))
if chunk_size > spool_length:
print(
f"Warning: Specified `chunk_size` ({chunk_size:.2f} seconds) exceeds the spool length "
f"({merged_sp.seconds:.2f} seconds). Adjusting `chunk_size` to match spool length."
f"({spool_length:.2f} seconds). Adjusting `chunk_size` to match spool length."
)
chunk_size = merged_sp.seconds
chunk_size = spool_length
```

Next, we need to determine the extent of artifacts introduced by low-pass filtering at the edges of each patch. To achieve this, we apply LF processing to a delta function patch, which contains a unit value at the center and zeros elsewhere. The distorted edges are then identified based on a defined threshold.
Expand All @@ -100,12 +103,11 @@ ind_1 = np.where(ind)[1][0]
ind_2 = np.where(ind)[1][-1]

# Get the total duration of the processed delta function patch in seconds
time_coord = delta_pa_lfp.get_coord('time')
delta_pa_lfp_seconds = dc.to_float((time_coord.max() - time_coord.min()))
delta_pa_lfp_length = delta_pa_lfp.seconds
# Convert the new time axis to absolute seconds, relative to the first timestamp
time_ax_abs = (new_time_ax - new_time_ax[0]) / np.timedelta64(1, "s")
# Center the time axis
time_ax_centered = time_ax_abs - delta_pa_lfp_seconds // 2
time_ax_centered = time_ax_abs - delta_pa_lfp_length // 2

# Calculate the maximum of edges in both sides (in seconds) where artifacts are present
edge = max(np.abs(time_ax_centered[ind_1]), np.abs(time_ax_centered[ind_2]))
Expand Down
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