From ba427c2dda3fff526e2fb19b4c811b93e880e419 Mon Sep 17 00:00:00 2001
From: Pranav Rai <rpranaviitk@gmail.com>
Date: Tue, 21 Apr 2026 23:12:20 +0100
Subject: [PATCH] Fix the IBL Cbin extractor so that it works with 4 split
 shanks as well I am taking the latest way of getting the sample shifts during
 the merge conflit.

---
 src/spikeinterface/extractors/cbin_ibl.py | 79 ++++++++++++++++++++++-
 1 file changed, 76 insertions(+), 3 deletions(-)

diff --git a/src/spikeinterface/extractors/cbin_ibl.py b/src/spikeinterface/extractors/cbin_ibl.py
index 2a53b999e3..4603095e29 100644
--- a/src/spikeinterface/extractors/cbin_ibl.py
+++ b/src/spikeinterface/extractors/cbin_ibl.py
@@ -1,4 +1,5 @@
 from pathlib import Path
+import re
 import warnings
 import numpy as np
 
@@ -9,6 +10,56 @@
 from spikeinterface.core.core_tools import define_function_from_class
 
 
+def _parse_spikeglx_meta_table(meta_value):
+    """Return parenthesized entries from a SpikeGLX meta value.
+
+    Accepts either the raw string form ``"(a)(b)(c)"`` or an already-parsed list.
+    """
+    if isinstance(meta_value, str):
+        return re.findall(r"\(([^()]*)\)", meta_value)
+    return list(meta_value)
+
+
+def _parse_saved_channel_subset(subset_text):
+    if subset_text is None or subset_text == "all":
+        return None
+    channels = []
+    for entry in subset_text.split(","):
+        if ":" in entry:
+            start, stop = entry.split(":")
+            channels.extend(np.arange(int(start), int(stop) + 1))
+        else:
+            channels.append(int(entry))
+    return np.asarray(channels, dtype="int64")
+
+
+def _get_saved_channel_indices(meta):
+    subset_text = meta.get("snsSaveChanSubset_orig")
+    if subset_text is None:
+        subset_text = meta.get("snsSaveChanSubset")
+    return _parse_saved_channel_subset(subset_text)
+
+
+def _read_spikeglx_probe(meta_file, meta):
+    """Build a Probe for a SpikeGLX meta, honoring IBL shank-split subsets."""
+    if "snsSaveChanSubset_orig" not in meta:
+        return probeinterface.read_spikeglx(meta_file)
+    from probeinterface.neuropixels_tools import _read_imro_string
+
+    probe = _read_imro_string(imro_str=meta["imroTbl"], imDatPrb_pn=meta.get("imDatPrb_pn"))
+    saved = _get_saved_channel_indices(meta)
+    if saved is not None:
+        saved = saved[saved < probe.get_contact_count()]
+        if saved.size != probe.get_contact_count():
+            probe = probe.get_slice(saved)
+    probe.annotate(serial_number=meta.get("imDatPrb_sn", meta.get("imProbeSN", None)))
+    probe.annotate(part_number=meta.get("imDatPrb_pn", None))
+    probe.annotate(port=meta.get("imDatPrb_port", None))
+    probe.annotate(slot=meta.get("imDatPrb_slot", None))
+    probe.set_device_channel_indices(np.arange(probe.get_contact_count()))
+    return probe
+
+
 class CompressedBinaryIblExtractor(BaseRecording):
     """Load IBL data as an extractor object.
 
@@ -99,7 +150,7 @@ def __init__(self, folder_path=None, load_sync_channel=False, stream_name="ap",
         self.set_channel_offsets(offsets)
 
         if not load_sync_channel:
-            probe = probeinterface.read_spikeglx(meta_file)
+            probe = _read_spikeglx_probe(meta_file, meta)
 
             if probe.shank_ids is not None:
                 self.set_probe(probe, in_place=True, group_mode="by_shank")
@@ -204,9 +255,31 @@ def extract_stream_info(meta_file, meta):
     info["stream_kind"] = stream_kind
     info["stream_name"] = stream_name
     info["units"] = units
-    info["channel_names"] = [txt.split(";")[0] for txt in meta["snsChanMap"]]
+
+    chan_map_entries = _parse_spikeglx_meta_table(meta["snsChanMap"])
+    # First entry is the header tuple like "(384,0,1)"; drop it when present.
+    if chan_map_entries and "," in chan_map_entries[0] and ";" not in chan_map_entries[0]:
+        chan_map_entries = chan_map_entries[1:]
+    full_channel_names = [entry.split(";")[0] for entry in chan_map_entries]
+
+    saved_indices = _get_saved_channel_indices(meta)
+    if saved_indices is not None and len(full_channel_names) >= saved_indices.max() + 1:
+        channel_names = [full_channel_names[i] for i in saved_indices]
+    else:
+        channel_names = full_channel_names
+
+    channel_offsets = np.zeros(num_chan)
+
+    if len(channel_names) != num_chan or channel_gains.shape[0] != num_chan:
+        raise ValueError(
+            "Parsed channel metadata does not match nSavedChans: "
+            f"channel_names={len(channel_names)}, channel_gains={channel_gains.shape[0]}, "
+            f"num_chan={num_chan}"
+        )
+
+    info["channel_names"] = channel_names
     info["channel_gains"] = channel_gains
-    info["channel_offsets"] = np.zeros(info["num_chan"])
+    info["channel_offsets"] = channel_offsets
     info["has_sync_trace"] = has_sync_trace
 
     return info