Merge branch 'main' of github.com:SpikeInterface/probeinterface into prepare_release

Author: alejoe91

.gitignore

@@ -25,3 +25,6 @@ dev_*
 .coverage
 cov.xml
 .DS_Store
+
+
+neuropixel_library_generated/*

.pre-commit-config.yaml

@@ -1,12 +1,12 @@
 repos:
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v5.0.0
     hooks:
     -   id: check-yaml
     -   id: end-of-file-fixer
     -   id: trailing-whitespace
 -   repo: https://github.com/psf/black
-    rev: 24.8.0
+    rev: 25.1.0
     hooks:
     -   id: black
         files: ^src/|^tests/

pyproject.toml

@@ -40,13 +40,14 @@ package-dir = {"probeinterface" = "src/probeinterface"}
 [project.optional-dependencies]
 
 test = [
+    "jsonschema",
     "pytest",
     "pytest-cov",
     "matplotlib",
     "scipy",
     "pandas",
     "h5py",
-    "zarr>=2.16.0"
+    "zarr>=2.16.0,<3.0.0"
 ]
 
 docs = [

resources/generate_cambridgeneurotech_libray.py

@@ -50,7 +50,8 @@
 # work_dir = '/home/samuel/Documents/SpikeInterface/2022-05-20-probeinterface_CambridgeNeurotech/'
 # work_dir = '/home/samuel/Documents/SpikeInterface/2022-10-18-probeinterface_CambridgeNeurotech/'
 # work_dir = '/home/samuel/OwnCloudCNRS/probeinterface/2023-06-14-probeinterface-CambridgeNeurotech/'
-work_dir = '/home/samuel/OwnCloudCNRS/probeinterface/2023-10-30-probeinterface-CambridgeNeurotech/'
+# work_dir = '/home/samuel/OwnCloudCNRS/probeinterface/2023-10-30-probeinterface-CambridgeNeurotech/'
+work_dir = '/home/samuel/NextcloudCNRS/probeinterface/2025-01-27-probeinterface-CambridgeNeurotech/'
 
 
 library_folder = '/home/samuel/Documents/SpikeInterface/probeinterface_library/cambridgeneurotech/'
@@ -59,7 +60,7 @@
 
 work_dir = Path(work_dir).absolute()
 
-export_folder = work_dir / 'export_2023_10_30'
+export_folder = work_dir / 'export_2025_01_27'
 probe_map_file = work_dir /  'ProbeMaps_Final2023.xlsx'
 probe_info_table_file = work_dir  / 'ProbesDataBase_Final2023.csv'
 
@@ -112,18 +113,21 @@ def get_contact_order(connector, probe_type):
     if probe_type == 'H5' or probe_type == 'H9':
         probe_type = 'H5 & H9'
 
-    #~ print(df[probe_type])
+    # print(df[probe_type])
     tmpList = []
     for i in df[probe_type].columns:
+        # print('i', i, len(df[probe_type].columns))
         if len(df[probe_type].columns) == 1:
             tmpList = np.flip(df[probe_type].values.astype(int).flatten())
         else:
             tmp = df[probe_type][i].values
             tmp = tmp[~np.isnan(tmp)].astype(int) # get rid of nan and convert to integer
             tmp = np.flip(tmp) # this flips the value to match index that goes from tip to headstage of the probe
+            # print('tmp', tmp)
             tmpList = np.append(tmpList, tmp)
             tmpList = tmpList.astype(int)
 
+    # print('tmpList', tmpList)
     return tmpList
 
 
@@ -200,7 +204,7 @@ def create_CN_figure(probe_name, probe):
     ax.spines['right'].set_visible(False) #remove external axis
     ax.spines['top'].set_visible(False) #remove external axis
 
-    ax.set_title('\n' +'CambridgeNeuroTech' +'\n'+  probe.annotations.get('name'), fontsize = 24)
+    ax.set_title('\n' +'CambridgeNeuroTech' +'\n'+  probe.annotations.get('model_name'), fontsize = 24)
 
     fig.tight_layout() #modif tight layout
 
@@ -242,6 +246,11 @@ def generate_all_probes():
     for i, probe_info in probe_info_table.iterrows():
         print(i, probe_info['part'])
 
+        # DEBUG
+        # if not probe_info['part'] in ('P-1', 'P-2'):
+        #     continue
+
+        # print(probe_info)
 
         if probe_info['shanks_n'] == 1:
             # one shank
@@ -254,16 +263,29 @@ def generate_all_probes():
         for connector in list(probe_info[probe_info.index.str.contains('ASSY')].dropna().index):
             probe_name = connector+'-'+probe_info['part']
 
-            #~ if probe_name != 'ASSY-77-H10':
-                #~ continue
+            # DEBUG
+            # if connector != 'ASSY-1':
+            #     continue
+
+
             print('  ', probe_name)
 
             contact_order = get_contact_order(connector = connector, probe_type = probe_info['part'])
 
+            # print(probe_unordered)
+            # print(probe_unordered.contact_ids)
+            # print(contact_order)
+            # print(probe_unordered.)
+            # fig, ax = plt.subplots()
+            # plot_probe(probe_unordered, ax=ax, with_contact_id=True)
+            # plt.show()
+
+
+
             sorted_indices = np.argsort(contact_order)
             probe = probe_unordered.get_slice(sorted_indices)
 
-            probe.annotate(name=probe_name, manufacturer='cambridgeneurotech')
+            probe.annotate(model_name=probe_name, manufacturer='cambridgeneurotech')
 
             # one based in cambridge neurotech
             contact_ids = np.arange(sorted_indices.size) + 1
@@ -272,6 +294,7 @@ def generate_all_probes():
 
             export_one_probe(probe_name, probe)
 
+        # break
 
 def synchronize_library():
 
@@ -309,6 +332,8 @@ def synchronize_library():
 
     # library_folder
 
+
+
 if __name__ == '__main__':
-    # generate_all_probes()
+    generate_all_probes()
     synchronize_library()

resources/generate_neuropixels_library.py

@@ -0,0 +1,106 @@
+import shutil
+from pathlib import Path
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+from probeinterface.neuropixels_tools import npx_descriptions, probe_part_number_to_probe_type, _make_npx_probe_from_description
+from probeinterface.plotting import plot_probe
+from probeinterface import write_probeinterface
+
+
+base_folder = Path("./neuropixels_library_generated")
+
+
+
+def generate_all_npx():
+
+    # if not base_folder.exists():
+    base_folder.mkdir(exist_ok=True)
+
+
+    for probe_number, probe_type in probe_part_number_to_probe_type.items():
+
+        if probe_number is None:
+            continue
+
+        if probe_number == "1110":
+            # the formula by the imrow table is wrong and more complicated
+            continue
+
+        probe_folder = base_folder / probe_number
+        probe_folder.mkdir(exist_ok=True)
+
+        print(probe_number, probe_type)
+
+        probe_description = npx_descriptions[probe_type]
+
+
+
+        num_shank = probe_description["shank_number"]
+        contact_per_shank = probe_description["ncols_per_shank"] * probe_description["nrows_per_shank"]
+        if num_shank == 1:
+            elec_ids = np.arange(contact_per_shank)
+            shank_ids = None
+        else:
+            elec_ids = np.concatenate([np.arange(contact_per_shank) for i in range(num_shank)])
+            shank_ids = np.concatenate([np.zeros(contact_per_shank) + i for i in range(num_shank)])
+
+        probe = _make_npx_probe_from_description(probe_description, elec_ids, shank_ids)
+
+        # ploting
+        fig, axs = plt.subplots(ncols=2)
+
+        ax = axs[0]
+        plot_probe(probe, ax=ax)
+        ax.set_title("")
+
+        ax.xaxis.set_visible(False)
+        ax.spines["top"].set_visible(False)
+        ax.spines["right"].set_visible(False)
+        ax.spines["bottom"].set_visible(False)
+
+        ax = axs[1]
+
+
+        # plot_probe(probe, ax=ax, text_on_contact=probe._contact_ids)
+        plot_probe(probe, ax=ax)
+        ax.set_title("")
+
+        yp = probe_description["y_pitch"]
+        ax.set_ylim(-yp*8, yp*13)
+        ax.yaxis.set_visible(False)
+        ax.spines["top"].set_visible(False)
+        ax.spines["right"].set_visible(False)
+        ax.spines["left"].set_visible(False)
+
+        n = probe.get_contact_count()
+
+        title = probe_number
+        title += f"\n{probe.manufacturer} - {probe.model_name}"
+        title += f"\n {n}ch"
+        if probe.shank_ids is not None:
+            num_shank = probe.get_shank_count()
+            title += f" - {num_shank}shanks"
+
+
+        fig.suptitle(title)
+
+        # plt.show()
+
+        fig.savefig(probe_folder / f"{probe_number}.png")
+
+        write_probeinterface(probe_folder / f"{probe_number}.json", probe)
+
+        plt.close(fig)
+
+
+
+
+
+
+
+
+
+if __name__ == "__main__":
+    generate_all_npx()

resources/probe.json.schema

@@ -26,10 +26,10 @@
           "annotations": {
             "type": "object",
             "properties": {
-              "name": { "type": "string" },
+              "model_name": { "type": "string" },
               "manufacturer": { "type": "string" }
             },
-            "required": ["name", "manufacturer"],
+            "required": ["model_name", "manufacturer"],
             "additionalProperties": true
           },
           "contact_annotations": {
@@ -71,14 +71,14 @@
               "anyOf": [
                 {
                   "type": "object",
-                  "properties": { "radius": { "type": "integer", "minimum": 0 } },
+                  "properties": { "radius": { "type": "number", "minimum": 0 } },
                   "required": ["radius"]
                 },
                 {
                   "type": "object",
                   "properties": {
-                    "width": { "type": "integer", "minimum": 0 },
-                    "height": { "type": "integer", "minimum": 0 }
+                    "width": { "type": "number", "minimum": 0 },
+                    "height": { "type": "number", "minimum": 0 }
                   },
                   "required": ["width"]
                 }
@@ -101,6 +101,10 @@
           "shank_ids": {
             "type": "array",
             "items": { "type": "string" }
+          },
+          "device_channel_indices": {
+            "type": "array",
+            "items": { "type": "integer" }
           }
         },
         "required": [

src/probeinterface/__init__.py

@@ -12,20 +12,23 @@
     write_prb,
     read_csv,
     write_csv,
-    read_imro,
-    write_imro,
     read_BIDS_probe,
     write_BIDS_probe,
     read_spikegadgets,
+    read_mearec,
+    read_nwb,
+    read_maxwell,
+    read_3brain,
+)
+from .neuropixels_tools import (
+    read_imro,
+    write_imro,
     read_spikeglx,
     parse_spikeglx_meta,
+    parse_spikeglx_snsGeomMap,
     get_saved_channel_indices_from_spikeglx_meta,
     read_openephys,
     get_saved_channel_indices_from_openephys_settings,
-    read_mearec,
-    read_nwb,
-    read_maxwell,
-    read_3brain,
 )
 from .utils import combine_probes
 from .generator import (