Draft public docs for Multi-Channel timeseries and Large Image workflows

benchmarks/create_ephys_data.ipynb

@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -29,7 +29,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -142,6 +142,76 @@
     "    mr.save_recording_generator(recgen, f'data/ephys_sim_neuropixels_{dur}s_384ch.h5')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Add channel names object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/Users/droumis/data/ephys_sim_neuropixels/ephys_sim_neuropixels_1s_384ch.h5 num_channels: 384\n",
+      "channels object already present.\n",
+      "/Users/droumis/data/ephys_sim_neuropixels/ephys_sim_neuropixels_10s_384ch.h5 num_channels: 384\n",
+      "channels object already present.\n",
+      "/Users/droumis/data/ephys_sim_neuropixels/ephys_sim_neuropixels_100s_384ch.h5 num_channels: 384\n",
+      "channels object added successfully.\n",
+      "channels object already present.\n",
+      "/Users/droumis/data/ephys_sim_neuropixels/ephys_sim_neuropixels_200s_384ch.h5 num_channels: 384\n",
+      "channels object added successfully.\n",
+      "channels object already present.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import h5py\n",
+    "from pathlib import Path\n",
+    "\n",
+    "durations = [1, 10, 100, 200]\n",
+    "\n",
+    "for dur in durations:\n",
+    "    # Open the existing HDF5 file in append mode\n",
+    "    H5_PATH = Path(f'~/data/ephys_sim_neuropixels/ephys_sim_neuropixels_{dur}s_384ch.h5').expanduser()\n",
+    "    with h5py.File(H5_PATH, 'a') as f:\n",
+    "        num_channels = f['channel_positions'].shape[0]\n",
+    "        print(H5_PATH, 'num_channels:', num_channels)\n",
+    "        # skip if 'channels' object already exists\n",
+    "        if 'channels' in f:\n",
+    "            print(\"channels object already present.\")\n",
+    "        else:\n",
+    "            f.create_dataset('channels', data=list(range(384)))\n",
+    "            print(\"channels object added successfully.\") \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "PosixPath('/Users/droumis/data/ephys_sim_neuropixels_10s_384ch.h5')"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "H5_PATH"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -152,7 +222,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "neuro-eeg-viewer",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -166,9 +236,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

workflows/multi_channel_timeseries/environment.yml

@@ -1,4 +1,4 @@
-name: neuro-multi-chan
+name: neuro-multi-chan-ts
 channels:
   - conda-forge
 dependencies:
@@ -10,15 +10,18 @@ dependencies:
   - datashader
   - numpy
   - pandas
-  - xarray
+  - xarray>=2024.5.0
   - ipykernel
-  - mne
   - jupyterlab
   - zarr
   - kerchunk
   - pyarrow
   - dask
   - jupyter_bokeh
+  - h5py
   - pip
   - pip:
-    - holonote
+    - holonote
+    - ndpyramid==0.2.0
+    - tsdownsample
+    - mne