From d6d478fae98913696045b04211cec41629f16748 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Tue, 25 Jul 2023 10:13:55 +0200 Subject: [PATCH] add responsive sizing and better spacing to eeg viewer --- ...725_responsive-sizing_better-spacing.ipynb | 219 +++ .../eeg-viewer/workflow_eeg-viewer.ipynb | 1369 +---------------- 2 files changed, 236 insertions(+), 1352 deletions(-) create mode 100644 workflows/eeg-viewer/dev/230725_responsive-sizing_better-spacing.ipynb diff --git a/workflows/eeg-viewer/dev/230725_responsive-sizing_better-spacing.ipynb b/workflows/eeg-viewer/dev/230725_responsive-sizing_better-spacing.ipynb new file mode 100644 index 0000000..e67f693 --- /dev/null +++ b/workflows/eeg-viewer/dev/230725_responsive-sizing_better-spacing.ipynb @@ -0,0 +1,219 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# EEG Viewer\n", + "![status](https://img.shields.io/badge/status-in%20progress-orange)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " \"eeg\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Summary\n", + "\n", + "This workflow is intended to demonstrate the visualization of a set of 1D EEG timeseries with HoloViz and Bokeh tools.\n", + "\n", + "For details specific to this workflow, such as goals, specifications, and bottlenecks, please see this workflow's [readme](./readme_eeg-viewer.md).\n", + "\n", + "For a summary of EEG research, data, and software, please see [neuro/wiki/EEG-notes](https://github.com/holoviz-topics/neuro/wiki/EEG-notes)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Imports and config" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "

Requirements

\n", + "

This workflow notebook requires the environment specified in this workflow directory.

\n", + "
\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import holoviews as hv; hv.extension('bokeh')\n", + "from holoviews.plotting.links import RangeToolLink\n", + "from neurodatagen.eeg import generate_eeg_powerlaw\n", + "from scipy.stats import zscore\n", + "import panel as pn; pn.extension()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generate simulated data\n", + "\n", + "The `generate_eeg_powerlaw` function synthesizes EEG data as high-pass filtered pink noise power law time series by default. The function returns a 2D numpy array of synthetic EEG data (in microvolts) shaped as (number of channels, total samples), a 1D time array (in seconds), and a list of channel names. Parameters such as the high-pass filter factor (in Hz) and an amplitude scaling factor allow customization of the generated data." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "n_channels = 25\n", + "n_seconds = 30\n", + "fs = 512\n", + "\n", + "data, time, channels = generate_eeg_powerlaw(n_channels, n_seconds, fs)\n", + "\n", + "print(f'shape: {data.shape} (n_channels, samples) ')\n", + "data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualize synthetic EEG data with minimap" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Set vertical spacing for EEG traces to avoid visual overlap\n", + "spacing = 1.2\n", + "offset = np.max(np.abs(data)) * spacing\n", + "\n", + "# Create a hv.Curve element per chan.\n", + "# Note: alternative is to call hv.Path once on offset-adjusted data, but \n", + "# then we couldn't independently apply formating to the channels (which \n", + "# we aren't doing yet, but we likely will in the future)\n", + "channel_curves = []\n", + "for i, channel_data in enumerate(data):\n", + " channel_curves.append(\n", + " hv.Curve((time, channel_data + (i * offset)), \"Time\").opts(\n", + " color=\"black\", line_width=1, tools=[\"hover\"], shared_axes=False))\n", + "\n", + "# Create mapping from yaxis location to ytick for each channel\n", + "# so we can have categorical-style labeling on a continuous axis.\n", + "# Note: this would/should change when we implement independent \n", + "# coordinates.\n", + "yticks = [(i * offset, ich) for i, ich in enumerate(channels)]\n", + "\n", + "# create a hook to set a predefined selection of RangeToolLink\n", + "max_ch_disp = 10\n", + "max_t_disp = 5\n", + "range_opts = []\n", + "\n", + "def xrange_hook(plot, element):\n", + " plot.handles['x_range'].end = max_t_disp\n", + "\n", + "def yrange_hook(plot, element):\n", + " plot.handles['y_range'].end = np.max(data[max_ch_disp-1,:] + ((max_ch_disp-1) * offset))\n", + " \n", + "if time.max() > max_t_disp:\n", + " range_opts.append(xrange_hook)\n", + "\n", + "if len(channel_curves) > max_ch_disp:\n", + " range_opts.append(yrange_hook)\n", + "\n", + "# Create an overlay of curves\n", + "eeg_viewer = hv.Overlay(channel_curves, kdims=\"Channel\").opts(\n", + " padding=0, xlabel=\"Time (s)\", ylabel=\"Channel\", #default_tools=['hover', 'pan', 'box_zoom', 'save', 'reset'],\n", + " yticks=yticks, show_legend=False, hooks=range_opts, aspect=1.5, responsive=True,\n", + " shared_axes=False)\n", + "\n", + "# Get the y positions of the yticks to use as yaxis of minimap image\n", + "y_positions, _ = zip(*yticks)\n", + "\n", + "# Compute z-scores across time for each channel\n", + "z_data = zscore(data, axis=1)\n", + "\n", + "# Generate the zscored image for the minimap using the y tick positions from the eeg_viewer\n", + "minimap = hv.Image((time, y_positions, z_data), [\"Time (s)\", \"Channel\"], \"Amplitude (uV)\")\n", + "\n", + "# Style the minimap \n", + "minimap = minimap.opts(\n", + " cmap=\"RdBu_r\", colorbar=False, xlabel='', alpha=.5, yticks=[yticks[0], yticks[-1]],\n", + " height=100, responsive=True, default_tools=[], shared_axes=False)\n", + "\n", + "# Create RangeToolLink between the minimap and the main EEG viewer \n", + "# (quirk: apply to just one eeg trace and it will apply to all. see HoloViews #4472)\n", + "RangeToolLink(minimap, list(eeg_viewer.values())[0], axes=[\"x\", \"y\"])\n", + "\n", + "# Display vertically\n", + "# layout = (eeg_viewer + minimap).cols(1).opts(shared_axes=False, merge_tools=False)\n", + "# eeg_app = pn.Row(layout).servable() # too much spacing between plots in served app\n", + "eeg_app = pn.Column(pn.Row(eeg_viewer, min_height=500), minimap).servable() # BUG Panel #5315: rangetool is variably active in the bokeh toolbar on eeg viewer plot.. not respecting shared_axes=False\n", + "eeg_app" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "
\n", + "

Tip:

\n", + "Hover near any border of the minimap, then click and drag to adjust the visible bounds in the EEG plot\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load and plot real data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/workflows/eeg-viewer/workflow_eeg-viewer.ipynb b/workflows/eeg-viewer/workflow_eeg-viewer.ipynb index e18ff9f..73d136b 100644 --- a/workflows/eeg-viewer/workflow_eeg-viewer.ipynb +++ b/workflows/eeg-viewer/workflow_eeg-viewer.ipynb @@ -50,1212 +50,9 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, 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metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import numpy as np\n", "import holoviews as hv; hv.extension('bokeh')\n", @@ -1276,39 +73,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "shape: (25, 15360) (n_channels, samples) \n" - ] - }, - { - "data": { - "text/plain": [ - "array([[ 84.42722634, 30.34719244, 5.22393437, ..., -10.80145429,\n", - " 49.24457926, -20.3452066 ],\n", - " [ 108.05387027, 30.26106509, 11.37492229, ..., -50.44795839,\n", - " -30.53834818, 16.01687823],\n", - " [ 53.12133901, 51.17480559, 42.03306468, ..., 68.96529254,\n", - " 22.83433864, 80.58174815],\n", - " ...,\n", - " [ 7.20033243, 25.04901892, 54.84328569, ..., 39.55741892,\n", - " 43.11086135, 70.97047299],\n", - " [ 21.19691413, -26.35453977, -41.42016342, ..., -71.72025934,\n", - " 26.43921826, 21.66218934],\n", - " [ 7.59592428, -43.97000938, -101.84756723, ..., -17.66192405,\n", - " -0.94337575, 29.73274791]])" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "n_channels = 25\n", "n_seconds = 30\n", @@ -1329,103 +96,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": {}, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": {}, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.holoviews_exec.v0+json": "", - "text/html": [ - "
\n", - "
\n", - "
\n", - "" - ], - "text/plain": [ - "HoloViews(Layout)" - ] - }, - "execution_count": 4, - "metadata": { - "application/vnd.holoviews_exec.v0+json": { - "id": "7354c973-e3fe-44e9-8ae6-6abc1704156c" - } - }, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# Set vertical spacing for EEG traces to avoid visual overlap\n", "spacing = 1.2\n", @@ -1439,7 +112,7 @@ "for i, channel_data in enumerate(data):\n", " channel_curves.append(\n", " hv.Curve((time, channel_data + (i * offset)), \"Time\").opts(\n", - " color=\"black\", line_width=1, tools=[\"hover\"]))\n", + " color=\"black\", line_width=1, tools=[\"hover\"], shared_axes=False))\n", "\n", "# Create mapping from yaxis location to ytick for each channel\n", "# so we can have categorical-style labeling on a continuous axis.\n", @@ -1466,8 +139,9 @@ "\n", "# Create an overlay of curves\n", "eeg_viewer = hv.Overlay(channel_curves, kdims=\"Channel\").opts(\n", - " width=800, height=600, padding=0, xlabel=\"Time (s)\", ylabel=\"Channel\",\n", - " yticks=yticks, show_legend=False, hooks=range_opts,)\n", + " padding=0, xlabel=\"Time (s)\", ylabel=\"Channel\", #default_tools=['hover', 'pan', 'box_zoom', 'save', 'reset'],\n", + " yticks=yticks, show_legend=False, hooks=range_opts, aspect=1.5, responsive=True,\n", + " shared_axes=False)\n", "\n", "# Get the y positions of the yticks to use as yaxis of minimap image\n", "y_positions, _ = zip(*yticks)\n", @@ -1478,29 +152,20 @@ "# Generate the zscored image for the minimap using the y tick positions from the eeg_viewer\n", "minimap = hv.Image((time, y_positions, z_data), [\"Time (s)\", \"Channel\"], \"Amplitude (uV)\")\n", "\n", - "# Style the minimap\n", + "# Style the minimap \n", "minimap = minimap.opts(\n", - " cmap=\"RdBu_r\", colorbar=False, width=800, height=100, xlabel='', alpha=.5, yticks=[yticks[0], yticks[-1]],)\n", + " cmap=\"RdBu_r\", colorbar=False, xlabel='', alpha=.5, yticks=[yticks[0], yticks[-1]],\n", + " height=100, responsive=True, default_tools=[], shared_axes=False)\n", "\n", "# Create RangeToolLink between the minimap and the main EEG viewer \n", "# (quirk: apply to just one eeg trace and it will apply to all. see HoloViews #4472)\n", "RangeToolLink(minimap, list(eeg_viewer.values())[0], axes=[\"x\", \"y\"])\n", "\n", "# Display vertically\n", - "layout = (eeg_viewer + minimap).cols(1).opts(shared_axes=False, merge_tools=False)\n", - "pn.panel(layout).servable()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "
\n", - "

Tip:

\n", - "Hover near any border of the minimap, then click and drag to adjust the visible bounds in the EEG plot\n", - "\n", - "
" + "# layout = (eeg_viewer + minimap).cols(1).opts(shared_axes=False, merge_tools=False)\n", + "# eeg_app = pn.Row(layout).servable() # too much spacing between plots in served app\n", + "eeg_app = pn.Column(pn.Row(eeg_viewer, min_height=500), minimap).servable() # BUG Panel #5315: rangetool is variably active in the bokeh toolbar on eeg viewer plot.. not respecting shared_axes=False\n", + "eeg_app" ] }, {