diff --git a/.gitignore b/.gitignore
index 0ee5de65..52a45ce4 100644
--- a/.gitignore
+++ b/.gitignore
@@ -30,3 +30,4 @@ uv.lock
# libraries
**/neuropixels_library_generated
**/cambridgeneurotech_library
+.codex
diff --git a/src/probeinterface/io.py b/src/probeinterface/io.py
index ad1a60ae..3de133fc 100644
--- a/src/probeinterface/io.py
+++ b/src/probeinterface/io.py
@@ -21,6 +21,7 @@
from . import __version__
from .probe import Probe
from .probegroup import ProbeGroup
+from .neuropixels_tools import build_neuropixels_probe
from .utils import import_safely
@@ -732,10 +733,35 @@ def write_csv(file, probe):
raise NotImplementedError
+_SPIKEGADGETS_NEUROPIXELS_FORMATS = {
+ # SpikeConfiguration.device -> (HardwareConfiguration device name, hardcoded part number, multi-probe x-shift um)
+ #
+ # The SpikeGadgets .rec XML does not include a probe part number. For each
+ # family (NP1 and NP2 4-shank) the listed catalogue variants share identical
+ # 2D geometry in the probeinterface catalogue (contact positions, pitch,
+ # stagger, shank spacing, shank width), differing only in metadata that
+ # probeinterface does not consume (ADC resolution, databus phase, gain,
+ # on-shank reference, shank thickness). So hardcoding one representative
+ # part number produces correct geometry. `model_name` and `description` are
+ # cleared on the sliced probe to avoid claiming a specific variant.
+ #
+ # NP1 family: NP1000, NP1001, PRB_1_2_0480_2, PRB_1_4_0480_1, PRB_1_4_0480_1_C.
+ # NP2 4-shank family: NP2010, NP2013, NP2014, NP2020, NP2021.
+ #
+ # The multi-probe x-shift is the horizontal offset applied to successive
+ # probes so they do not overlap when plotted. Chosen larger than the probe
+ # width: NP1 is ~70 um wide (250 um shift leaves a generous gap); NP2
+ # 4-shank is ~820 um wide (4 shanks * 250 um shank pitch + ~70 um shank
+ # width), so 1000 um leaves ~180 um of gap.
+ "neuropixels1": ("NeuroPixels1", "NP1000", 250.0),
+ "neuropixels2": ("NeuroPixels2", "NP2014", 1000.0),
+}
+
+
def read_spikegadgets(file: str | Path, raise_error: bool = True) -> ProbeGroup:
"""
Find active channels of the given Neuropixels probe from a SpikeGadgets .rec file.
- SpikeGadgets headstages support up to three Neuropixels 1.0 probes (as of March 28, 2024),
+ SpikeGadgets headstages support up to three Neuropixels probes (1.0 or 2.0),
and information for all probes will be returned in a ProbeGroup object.
@@ -749,146 +775,62 @@ def read_spikegadgets(file: str | Path, raise_error: bool = True) -> ProbeGroup:
probe_group : ProbeGroup object
"""
- # ------------------------- #
- # Npix 1.0 constants #
- # ------------------------- #
- TOTAL_NPIX_ELECTRODES = 960
- MAX_ACTIVE_CHANNELS = 384
- CONTACT_WIDTH = 16 # um
- CONTACT_HEIGHT = 20 # um
- # ------------------------- #
-
- # Read the header and get Configuration elements
header_txt = parse_spikegadgets_header(file)
root = ElementTree.fromstring(header_txt)
hconf = root.find("HardwareConfiguration")
sconf = root.find("SpikeConfiguration")
- # Get number of probes present (each has its own Device element)
- probe_configs = [device for device in hconf if device.attrib["name"] == "NeuroPixels1"]
+ # SpikeConfiguration.device selects the Neuropixels family. Default to NP1
+ # when absent to preserve behavior for older files that predate the attribute.
+ sconf_device = (sconf.attrib.get("device", "") if sconf is not None else "").lower()
+ if sconf_device not in _SPIKEGADGETS_NEUROPIXELS_FORMATS:
+ sconf_device = "neuropixels1"
+ hc_device_name, part_number, multi_probe_x_shift_um = _SPIKEGADGETS_NEUROPIXELS_FORMATS[sconf_device]
+
+ probe_configs = [d for d in hconf if d.attrib.get("name") == hc_device_name]
n_probes = len(probe_configs)
if n_probes == 0:
if raise_error:
- raise Exception("No Neuropixels 1.0 probes found")
+ raise Exception(f"No {hc_device_name} devices found in SpikeGadgets .rec header")
return None
- # Container to store Probe objects
probe_group = ProbeGroup()
for curr_probe in range(1, n_probes + 1):
- probe_config = probe_configs[curr_probe - 1]
-
- # Get number of active channels from probe Device element
- active_channel_str = [option for option in probe_config if option.attrib["name"] == "channelsOn"][0].attrib[
- "data"
- ]
- active_channels = [int(ch) for ch in active_channel_str.split(" ") if ch]
- n_active_channels = sum(active_channels)
- assert len(active_channels) == TOTAL_NPIX_ELECTRODES
- assert n_active_channels <= MAX_ACTIVE_CHANNELS
-
- """
- Within the SpikeConfiguration header element (sconf), there is a SpikeNTrode element
- for each electrophysiology channel that contains information relevant to scaling and
- otherwise displaying the information from that channel, as well as the id of the electrode
- from which it is recording ('id').
-
- Nested within each SpikeNTrode element is a SpikeChannel element with information about
- the electrode dynamically connected to that channel. This contains information relevant
- for spike sorting, i.e., its spatial location along the probe shank and the hardware channel
- to which it is connected.
-
- Excerpt of a sample SpikeConfiguration element:
-
-
-
-
-
- ...
-
- """
- # Find all channels/electrodes that belong to the current probe
- contact_ids = []
- device_channels = []
- positions = np.zeros((n_active_channels, 2))
-
- nt_i = 0 # Both probes are in sconf, so need an independent counter of probe electrodes while iterating through
+ # SpikeNTrode elements are the authoritative list of recorded electrodes.
+ # Each id is "<1-based electrode number>"; the catalogue uses
+ # 0-based electrode indices, so catalogue_index = electrode_number - 1.
+ # This holds for both NP1 (up to 960 electrodes) and NP2 4-shank (up to
+ # 5120 electrodes, shank-major in the catalogue: s0e0..s0e1279, s1e0..).
+ #
+ # The probe number is assumed to be a single digit (1, 2, or 3). This
+ # matches the documented SpikeGadgets limit of three simultaneous
+ # Neuropixels probes per headstage. If that limit ever changes, the
+ # id-to-(probe, electrode) split will need to be revisited.
+ electrode_to_hwchan = {}
for ntrode in sconf:
electrode_id = ntrode.attrib["id"]
- if int(electrode_id[0]) == curr_probe: # first digit of electrode id is probe number
- contact_ids.append(electrode_id)
- positions[nt_i, :] = (ntrode[0].attrib["coord_ml"], ntrode[0].attrib["coord_dv"])
- device_channels.append(ntrode[0].attrib["hwChan"])
- nt_i += 1
- assert len(contact_ids) == n_active_channels
-
- # Construct Probe object
- probe = Probe(ndim=2, si_units="um", model_name="Neuropixels 1.0", manufacturer="IMEC")
- probe.set_contacts(
- contact_ids=contact_ids,
- positions=positions,
- shapes="square",
- shank_ids=None,
- shape_params={"width": CONTACT_WIDTH, "height": CONTACT_HEIGHT},
- )
+ if int(electrode_id[0]) == curr_probe:
+ catalogue_index = int(electrode_id[1:]) - 1
+ hw_chan = int(ntrode[0].attrib["hwChan"])
+ electrode_to_hwchan[catalogue_index] = hw_chan
- # Wire it (i.e., point contact/electrode ids to corresponding hardware/channel ids)
- probe.set_device_channel_indices(device_channels)
+ active_indices = np.array(sorted(electrode_to_hwchan.keys()))
- # Create a nice polygon background when plotting the probes
- x_min = positions[:, 0].min()
- x_max = positions[:, 0].max()
- x_mid = 0.5 * (x_max + x_min)
- y_min = positions[:, 1].min()
- y_max = positions[:, 1].max()
- polygon_default = [
- (x_min - 20, y_min - CONTACT_HEIGHT / 2),
- (x_mid, y_min - 100),
- (x_max + 20, y_min - CONTACT_HEIGHT / 2),
- (x_max + 20, y_max + 20),
- (x_min - 20, y_max + 20),
- ]
- probe.set_planar_contour(polygon_default)
+ full_probe = build_neuropixels_probe(part_number)
+ probe = full_probe.get_slice(active_indices)
+
+ # Clear part-number-specific metadata since we don't know the actual part number.
+ probe.model_name = ""
+ probe.description = ""
+
+ device_channels = np.array([electrode_to_hwchan[idx] for idx in active_indices])
+ probe.set_device_channel_indices(device_channels)
- # If there are multiple probes, they must be shifted such that they don't occupy the same coordinates.
- probe.move([250 * (curr_probe - 1), 0])
+ # Shift multiple probes so they don't overlap when plotted
+ probe.move([multi_probe_x_shift_um * (curr_probe - 1), 0])
- # Add the probe to the probe container
probe_group.add_probe(probe)
return probe_group
diff --git a/tests/data/spikegadgets/SpikeGadgets_test_data_NP2_4shank_20260122_header_only.rec b/tests/data/spikegadgets/SpikeGadgets_test_data_NP2_4shank_20260122_header_only.rec
new file mode 100644
index 00000000..07ebe2e3
--- /dev/null
+++ b/tests/data/spikegadgets/SpikeGadgets_test_data_NP2_4shank_20260122_header_only.rec
@@ -0,0 +1,1246 @@
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+U a'W+ `@ p PPpP@ P p@`P Pp@` `0` 0P0`
+
`P00` P P`p0`@0 P``p00p0P 0@ 00P pPpP 0p@p00pp@P 0 `` 00 @`0 PP@@Ppp 0`p @@@ P0p@@@ @P pP 0 PP@ p0@ 0pP @p@pp@ 0@0 @ 0`00`P`p0P ppP@` P p0` P@ Pp @PP@P0 ` 0 `` U 1W+ 0p0 @0 @ `
+0 PP @@ P@@P0
0p p0P` 0P @@`p `P p0
@ jPp0@` `pPP p0`@ pp@ P` ` P p@0@@p`@ pPP ` p@p
p@ 0 P 0pP@ @ ` ``@`00 0 0P`P`P0@`@P @p`P00 `pP P @ P P@`P 0 Pp0U e scheme.
+ assert 1 <= probe.get_shank_count() <= 4
+ assert all(cid.startswith("s") and "e" in cid for cid in probe.contact_ids)
+
+
if __name__ == "__main__":
test_parse_meta()
test_neuropixels_1_reader()
+ test_neuropixels_2_4shank_reader()