implement ephys-viz interface and provide an example

examples/YutaMouse41-ephys-viz.ipynb

@@ -0,0 +1,101 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## YutaMouse41-ephys-viz\n",
+    "\n",
+    "To use this notebook you will need to install the ephys_viz package.\n",
+    "\n",
+    "Roughly speaking that involves installing ephys_viz from PyPI and installing the reactpoya_jup notebook and/or lab extensions.\n",
+    "\n",
+    "See: https://github.com/flatironinstitute/ephys-viz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Imports and initialization of ephys-viz in this notebook\n",
+    "import pynwb\n",
+    "from pynwb import NWBHDF5IO\n",
+    "from nwbwidgets import nwb2widget\n",
+    "import ephys_viz as ev\n",
+    "from nwbwidgets.ephys_viz_interface import ephys_viz_neurodata_vis_spec as vis_spec\n",
+    "ev.init_jupyter()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# You need to have an .nwb file on your computer\n",
+    "file_name = 'YutaMouse41-150903.nwb'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Lazy-load the nwb file\n",
+    "nwb_io = NWBHDF5IO(file_name, mode='r')\n",
+    "nwb = nwb_io.read()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Display the LFP using ephys-viz\n",
+    "nwb2widget(nwb.fields['processing']['ecephys']['LFP'], vis_spec)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# The ephys-viz widget is integrated into nwbwidgets\n",
+    "nwb2widget(nwb, vis_spec)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

nwbwidgets/__init__.py

@@ -1 +1,2 @@
 from .view import nwb2widget
+from .ephys_viz_interface import ephys_viz_neurodata_vis_spec

nwbwidgets/ephys_viz_interface.py

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+import matplotlib.pyplot as plt
+import ipywidgets as widgets
+import pynwb
+from pynwb import TimeSeries
+import numpy as np
+from nwbwidgets import view
+from pynwb.ecephys import LFP
+from .view import default_neurodata_vis_spec
+import spikeextractors as se
+from pynwb.ecephys import LFP
+
+ephys_viz_neurodata_vis_spec = default_neurodata_vis_spec
+def _set_spec():
+    ephys_viz_neurodata_vis_spec[pynwb.ecephys.LFP] = show_lfp
+
+def show_lfp(node: LFP, **kwargs):
+    import spikeextractors as se
+    import ephys_viz as ev
+    try:
+        recording = LFPRecordingExtractor(lfp_node=node)
+    except:
+        return widgets.Text('Problem creating LFPRecordingExtractor')
+    return ev.TimeseriesView(
+        recording=recording,
+        initial_y_scale_factor=5
+    ).show(render=False)
+
+class LFPRecordingExtractor(se.RecordingExtractor):
+    def __init__(self, lfp_node: LFP):
+        super().__init__()
+        lfp = list(lfp_node.electrical_series.values())[0]    
+        self._samplerate = lfp.rate
+        self._data = lfp.data
+        self._num_channels = self._data.shape[1]
+        self._num_timepoints = self._data.shape[0]
+
+    def get_channel_ids(self):
+        return list(range(self._num_channels))
+
+    def get_num_frames(self):
+        return self._num_timepoints
+
+    def get_sampling_frequency(self):
+        return self._samplerate
+
+    def get_traces(self, channel_ids=None, start_frame=None, end_frame=None):
+        if start_frame is None:
+            start_frame = 0
+        if end_frame is None:
+            end_frame = self.get_num_frames()
+        if channel_ids is None:
+            channel_ids = self.get_channel_ids()
+        return self._data[start_frame:end_frame, :][:, channel_ids].T
+
+_set_spec()