How to work with multi-recording HDF5 files

A single HDF5 file can contain multiple recordings (e.g. two probes from the same session) and multiple pyramidal scales of each recording. This guide shows how to list, select, and read from them.

Inspect an HDF5 file

from lfpack import LFPackReader

# List recordings in the file
recordings = LFPackReader.recordings("multi.lf.h5")
print(recordings)   # e.g. ['probe00', 'probe01']

# List available scales for a recording
scales = LFPackReader.scales("multi.lf.h5", "probe00")
print(scales)       # e.g. [0, 1, 2]  (0 = full resolution)

Open a specific recording

sr = LFPackReader("multi.lf.h5", recording="probe00")
traces = sr[0:1000]

If the file contains only one recording, recording can be omitted and it is selected automatically.

Open a downsampled scale

# Scale 1 is spatially downsampled (half the channels)
sr = LFPackReader("multi.lf.h5", recording="probe00", scale=1)

Scale 0 is always the full-resolution recording. Higher scale indices correspond to progressively coarser spatial representations.

Write a multi-recording file

Use compress_to_h5 (not compress_bin_to_h5) and call it once per recording, passing the same output path each time:

from lfpack import compress_to_h5
import numpy as np

# First probe
data_a = np.load("probe00_lfp.npy")   # (nc, ns) float32
compress_to_h5(data_a, fs=250.0, h5_file="session.lf.h5", recording="probe00")

# Second probe — appended to the same file
data_b = np.load("probe01_lfp.npy")
compress_to_h5(data_b, fs=250.0, h5_file="session.lf.h5", recording="probe01")

See compress_to_h5 for the full parameter list.