Merge branch 'main' into change_to_hatchling

Author: h-mayorquin

.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/

README.md

@@ -73,7 +73,7 @@ In addition, ProbeInterface also offers the following features:
 
 ## Documentation
 
-Detailed documentation of the latest PyPI release of ProbeInterface can be found [here](https://probeinterface.readthedocs.io/en/0.2.18).
+Detailed documentation of the latest PyPI release of ProbeInterface can be found [here](https://probeinterface.readthedocs.io/en/stable).
 
 Detailed documentation of the development version of ProbeInterface can be found [here](https://probeinterface.readthedocs.io/en/latest).
 

doc/release_notes.rst

@@ -6,6 +6,8 @@ Release notes
 .. toctree::
    :maxdepth: 1
 
+   releases/0.2.26.rst
+   releases/0.2.25.rst
    releases/0.2.24.rst
    releases/0.2.23.rst
    releases/0.2.22.rst

doc/releases/0.2.25.rst

@@ -0,0 +1,27 @@
+probeinterface 0.2.25
+---------------------
+
+Feb, 6th 2025
+
+
+Features
+^^^^^^^^
+
+* Add cambridge neurotech adaptor to wiring > RHD2164 (#304)
+* Refactor neuropixel in a separate file and generate the NP library (#316)
+* Regenerate ASSY-1-P1 and ASSY-1-P2 probes (#317)
+
+Bug fixes
+^^^^^^^^^
+
+* Fix OpenEphys interface issue with multiple probes of which some are disabled (#308)
+* Update schema to floats for radius, width, height (#296, #297)
+
+Tests
+^^^^^
+
+* Add json validation to tests (#310)
+
+Packaging
+^^^^^^^^^
+* Upper bound to zarr version (#314)

doc/releases/0.2.26.rst

@@ -0,0 +1,27 @@
+probeinterface 0.2.26
+---------------------
+
+Mar, 11th 2025
+
+
+Features
+^^^^^^^^
+
+* Support OneBox processor for Neuropixels-Open Ephys (#327)
+* Wiring pathway for Cambridge A64 adaptor with 2x intan RHD2132 (#306)
+* Add support for NP2020 (Neuropixels 2.0 - Quad Base) (#323)
+
+Bug fixes
+^^^^^^^^^
+
+* Fix NP contour from Open Ephys and remove `oe_x_shift`(#323)
+
+Tests
+^^^^^
+
+* Add test file and test for for NP2 - Quad Base (#328)
+
+Packaging
+^^^^^^^^^
+* Add json schema to core and make jsonschema dependency optional (#326)
+* Rename `-` to `_` in wiring_references  (#320)

examples/ex_11_automatic_wiring.py

@@ -41,31 +41,35 @@
 
 ##############################################################################
 # In order to ease this process, `probeinterface` also includes some commonly
-# used wirings based on standard connectors. In our case, we can simply use:
+# used wirings based on standard connectors. We created references and spreadsheets
+# showing how these wirings are computed at `probeinterface/resources/wiring_references
+# <https://github.com/SpikeInterface/probeinterface/tree/9776684948e3ceba71601e5c0f90c2672f665234/resources>`_.
+# If we have a Intan RHD2132 Headstage attached to a NeuroNexus H32 Connector, we can
+# import this wiring as follows:
 
 probe.wiring_to_device('H32>RHD2132')
 print(probe.device_channel_indices)
 
 ##############################################################################
 # In this figure we have 2 numbers for each contact:
-#    * the upper number "prbXX" is the Neuronexus index (one-based)
+#    * the upper number "prbXX" is the contact id (one-based, from NeuroNexus)
 #    * the lower "devXX" is the channel on the Intan device (zero-based)
 
 fig, ax = plt.subplots(figsize=(5, 15))
 plot_probe(probe, with_contact_id=True, with_device_index=True, ax=ax)
 
 
-plt.show()
-
-"""
-Available wiring "pathways"
----------------------------
-
-The available pathways can be found in the `probeinterface.wiring <>`_ module.
-
-The following pathways are available:
-"""
+##############################################################################
+# Available wiring "pathways"
+# ---------------------------
+#
+# The available pathways can be found in the `probeinterface.wiring <https://github.com/SpikeInterface/probeinterface/blob/main/src/probeinterface/wiring.py>`_ module.
+#
+# The following pathways are available:
+#
 
 from probeinterface import get_available_pathways
 
 print(get_available_pathways())
+
+plt.show()

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "probeinterface"
-version = "0.2.24"
+version = "0.2.26"
 authors = [
   { name="Samuel Garcia", email="sam.garcia.die@gmail.com" },
   { name="Alessio Buccino", email="alessiop.buccino@gmail.com" },
@@ -37,16 +37,18 @@ packages = ["src/probeinterface"]
 [tool.hatch.build.targets.sdist]
 packages = ["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()