Refactor neuropixel in a separate file and generate the NP library.

.gitignore

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

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()

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 (