First test run

.github/workflows/update-hf.yml

@@ -17,4 +17,4 @@ jobs:
         env:
           HF_USER: ${{ secrets.HF_USER }}
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
-        run: git push https://$HF_USER:$HF_TOKEN@huggingface.co/spaces/voila-dashboards/voila-huggingface main --force
+        run: git push https://$HF_USER:$HF_TOKEN@huggingface.co/spaces/camilleseab/surveillance main --force

Dockerfile

@@ -17,4 +17,4 @@ RUN mamba env create --prefix $HOME/env  -f ./environment.yml
 EXPOSE 7860
 WORKDIR $HOME/app
 
-CMD mamba run -p $HOME/env --no-capture-output voila --no-browser notebooks/
+CMD mamba run -p $HOME/env --no-capture-output voila --no-browser app.ipynb

app.ipynb

@@ -0,0 +1,114 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ipywidgets as widgets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "DEFAULTS = {\n",
+    "    'size': 640,\n",
+    "    'heading': 140,\n",
+    "    'pitch': 10,\n",
+    "    'fov': 50\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "output = widgets.Output()\n",
+    "lbl_style = {'description_width': '200px'}\n",
+    "layout = widgets.Layout(width='600px')\n",
+    "location = widgets.Text(value='33rd & Loch Raven Baltimore MD',\n",
+    "                        description='Location',\n",
+    "                        layout=layout,\n",
+    "                        style=lbl_style)\n",
+    "size = widgets.IntSlider(value=DEFAULTS['size'],\n",
+    "                         min=100,\n",
+    "                         max=1024,\n",
+    "                         layout=layout,\n",
+    "                         style=lbl_style,\n",
+    "                         description='Image size')\n",
+    "heading = widgets.IntSlider(value=DEFAULTS['heading'],\n",
+    "                            min=0,\n",
+    "                            max=360,\n",
+    "                            layout=layout,\n",
+    "                            style=lbl_style,\n",
+    "                            description='Heading (rotation)')\n",
+    "pitch = widgets.IntSlider(value=DEFAULTS['pitch'],\n",
+    "                          min=0,\n",
+    "                          max=40,\n",
+    "                          layout=layout,\n",
+    "                          style=lbl_style,\n",
+    "                          description='Pitch (tilt)')\n",
+    "fov = widgets.IntSlider(value=DEFAULTS['fov'],\n",
+    "                        min=10,\n",
+    "                        max=120,\n",
+    "                        layout=layout,\n",
+    "                        style=lbl_style,\n",
+    "                        description='Field of view (zoom)')\n",
+    "\n",
+    "button = widgets.Button(description='Get image')\n",
+    "\n",
+    "display(location, size, heading, pitch, fov, button, output)\n",
+    "\n",
+    "\n",
+    "def button_click(b):\n",
+    "    with output:\n",
+    "        output.clear_output()\n",
+    "        txt = f'test: location = {location.value}'\n",
+    "        print(txt)\n",
+    "    return txt\n",
+    "\n",
+    "sv_img = button.on_click(button_click)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "voila",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

environment.yml

@@ -2,19 +2,14 @@ name: voila
 channels:
   - conda-forge
 dependencies:
-  - python=3.10
+  - python=3.11.5
   - ipywidgets
   - ipykernel
-  - pandas
   - pip
-  - bokeh
-  - bqplot
-  - ipympl=0.9.2
-  - jupyterlab-fasta
-  - matplotlib
-  - scipy
-  - vega_datasets
-  - ipyvolume
+  - ultralytics=8.0.186
+  - pillow
+  - python-dotenv
+  - opencv
 
   - pip:
     - voila==0.5.0

notebooks/basics.ipynb

@@ -1,88 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "source": [
-    "# So easy, *voilà*!\n",
-    "\n",
-    "In this example notebook, we demonstrate how Voilà can render Jupyter notebooks with interactions requiring a roundtrip to the kernel."
-   ],
-   "metadata": {}
-  },
-  {
-   "cell_type": "markdown",
-   "source": [
-    "## Jupyter Widgets"
-   ],
-   "metadata": {}
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "source": [
-    "import ipywidgets as widgets\n",
-    "\n",
-    "slider = widgets.FloatSlider(description='$x$')\n",
-    "text = widgets.FloatText(disabled=True, description='$x^2$')\n",
-    "\n",
-    "def compute(*ignore):\n",
-    "    text.value = str(slider.value ** 2)\n",
-    "\n",
-    "slider.observe(compute, 'value')\n",
-    "\n",
-    "slider.value = 4\n",
-    "\n",
-    "widgets.VBox([slider, text])"
-   ],
-   "outputs": [],
-   "metadata": {}
-  },
-  {
-   "cell_type": "markdown",
-   "source": [
-    "## Basic outputs of code cells"
-   ],
-   "metadata": {}
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "source": [
-    "import pandas as pd\n",
-    "\n",
-    "iris = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')\n",
-    "iris"
-   ],
-   "outputs": [],
-   "metadata": {}
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "source": [],
-   "outputs": [],
-   "metadata": {}
-  }
- ],
- "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": "3.8.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}

notebooks/bqplot.ipynb

@@ -1,62 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# So easy, *voilà*!\n",
-    "\n",
-    "In this example notebook, we demonstrate how Voilà can render custom Jupyter widgets such as [bqplot](https://github.com/bloomberg/bqplot). "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings('ignore')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from bqplot import pyplot as plt\n",
-    "\n",
-    "plt.figure(1, title='Line Chart')\n",
-    "np.random.seed(0)\n",
-    "n = 200\n",
-    "x = np.linspace(0.0, 10.0, n)\n",
-    "y = np.cumsum(np.random.randn(n))\n",
-    "plt.plot(x, y)\n",
-    "plt.show()"
-   ]
-  }
- ],
- "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": "3.7.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

notebooks/dashboard.ipynb

@@ -1,148 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This demo uses Voilà to render a notebook to a custom HTML page using gridstack.js for the layout of each output. In the cell metadata you can change the default cell with and height (in grid units between 1 and 12) by specifying.\n",
-    " * `grid_row`\n",
-    " * `grid_columns`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "n = 200\n",
-    "\n",
-    "x = np.linspace(0.0, 10.0, n)\n",
-    "y = np.cumsum(np.random.randn(n)*10).astype(int)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import ipywidgets as widgets"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "label_selected = widgets.Label(value=\"Selected: 0\")\n",
-    "label_selected"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "grid_columns": 8,
-    "grid_rows": 4
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from bqplot import pyplot as plt\n",
-    "import bqplot\n",
-    "\n",
-    "fig = plt.figure( title='Histogram')\n",
-    "np.random.seed(0)\n",
-    "hist = plt.hist(y, bins=25)\n",
-    "hist.scales['sample'].min = float(y.min())\n",
-    "hist.scales['sample'].max = float(y.max())\n",
-    "display(fig)\n",
-    "fig.layout.width = 'auto'\n",
-    "fig.layout.height = 'auto'\n",
-    "fig.layout.min_height = '300px' # so it shows nicely in the notebook\n",
-    "fig.layout.flex = '1'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "grid_columns": 12,
-    "grid_rows": 6
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from bqplot import pyplot as plt\n",
-    "import bqplot\n",
-    "\n",
-    "fig = plt.figure( title='Line Chart')\n",
-    "np.random.seed(0)\n",
-    "n = 200\n",
-    "p = plt.plot(x, y)\n",
-    "fig"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fig.layout.width = 'auto'\n",
-    "fig.layout.height = 'auto'\n",
-    "fig.layout.min_height = '300px' # so it shows nicely in the notebook\n",
-    "fig.layout.flex = '1'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "brushintsel = bqplot.interacts.BrushIntervalSelector(scale=p.scales['x'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def update_range(*args):\n",
-    "    label_selected.value = \"Selected range {}\".format(brushintsel.selected)\n",
-    "    mask = (x > brushintsel.selected[0]) & (x < brushintsel.selected[1])\n",
-    "    hist.sample = y[mask]\n",
-    "    \n",
-    "brushintsel.observe(update_range, 'selected')\n",
-    "fig.interaction = brushintsel"
-   ]
-  }
- ],
- "metadata": {
-  "celltoolbar": "Edit 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": "3.6.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

notebooks/ipympl.ipynb

@@ -1,110 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# So easy, *voilà*!\n",
-    "\n",
-    "In this example notebook, we demonstrate how Voilà can render custom interactive matplotlib figures using the [ipympl](https://github.com/matplotlib/ipympl) widget."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%matplotlib widget\n",
-    "import ipympl\n",
-    "\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "x = np.linspace(0, 2 * np.pi, 500)\n",
-    "y1 = np.sin(x)\n",
-    "y2 = np.sin(3 * x)\n",
-    "\n",
-    "fig, ax = plt.subplots()\n",
-    "ax.fill(x, y1, 'b', x, y2, 'r', alpha=0.3)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "plt.style.use('ggplot')\n",
-    "\n",
-    "fig, axes = plt.subplots(ncols=2, nrows=2)\n",
-    "ax1, ax2, ax3, ax4 = axes.ravel()\n",
-    "\n",
-    "# scatter plot (Note: `plt.scatter` doesn't use default colors)\n",
-    "x, y = np.random.normal(size=(2, 200))\n",
-    "ax1.plot(x, y, 'o')\n",
-    "\n",
-    "# sinusoidal lines with colors from default color cycle\n",
-    "L = 2 * np.pi\n",
-    "x = np.linspace(0, L)\n",
-    "ncolors = len(plt.rcParams['axes.prop_cycle'])\n",
-    "shift = np.linspace(0, L, ncolors, endpoint=False)\n",
-    "for s in shift:\n",
-    "    ax2.plot(x, np.sin(x + s), '-')\n",
-    "ax2.margins(0)\n",
-    "\n",
-    "# bar graphs\n",
-    "x = np.arange(5)\n",
-    "y1, y2 = np.random.randint(1, 25, size=(2, 5))\n",
-    "width = 0.25\n",
-    "ax3.bar(x, y1, width)\n",
-    "ax3.bar(x + width, y2, width,\n",
-    "        color=list(plt.rcParams['axes.prop_cycle'])[2]['color'])\n",
-    "ax3.set_xticks(x + width)\n",
-    "ax3.set_xticklabels(['a', 'b', 'c', 'd', 'e'])\n",
-    "\n",
-    "# circles with colors from default color cycle\n",
-    "for i, color in enumerate(plt.rcParams['axes.prop_cycle']):\n",
-    "    xy = np.random.normal(size=2)\n",
-    "    ax4.add_patch(plt.Circle(xy, radius=0.3, color=color['color']))\n",
-    "\n",
-    "ax4.axis('equal')\n",
-    "ax4.margins(0)\n",
-    "\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "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": "3.7.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

notebooks/ipyvolume.ipynb

@@ -1,44 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# So easy, *voilà*!\n",
-    "\n",
-    "In this example notebook, we demonstrate how Voilà can render custom Jupyter widgets such as [ipyvolume](https://github.com/maartenbreddels/ipyvolume). "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import ipyvolume as ipv\n",
-    "ipv.examples.example_ylm();"
-   ]
-  }
- ],
- "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": "3.7.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

notebooks/mimerenderers.ipynb

@@ -1,489 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ff203dda-d0f3-48a8-95d5-587fbe1acae8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from IPython.display import display\n",
-    "from IPython.display import (\n",
-    "    HTML, Image, Latex, Math, Markdown, SVG\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "83934e25-4c2a-4521-b128-f4da77793fe8",
-   "metadata": {},
-   "source": [
-    "## Text"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4c0ef0c2-a7c2-4aee-b047-d009e9794ef9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "text = \"\"\"Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam urna\n",
-    "libero, dictum a egestas non, placerat vel neque. In imperdiet iaculis fermentum. \n",
-    "Vestibulum ante ipsum primis in faucibus orci luctus et ultrices posuere cubilia \n",
-    "Curae; Cras augue tortor, tristique vitae varius nec, dictum eu lectus. Pellentesque \n",
-    "id eleifend eros. In non odio in lorem iaculis sollicitudin. In faucibus ante ut \n",
-    "arcu fringilla interdum. Maecenas elit nulla, imperdiet nec blandit et, consequat \n",
-    "ut elit.\"\"\"\n",
-    "print(text)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9f841613-56a3-4b9f-a342-929f77534159",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import sys; print('this is stderr', file=sys.stderr)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ff9bcbcb-8b11-4215-a5bd-a82265ab63f2",
-   "metadata": {},
-   "source": [
-    "## HTML"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "317c2b55-881f-436c-8cc5-1753e8ebb4b6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "div = HTML('<div style=\"width:100px;height:100px;background:grey;\" />')\n",
-    "div"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e410f2d6-d6be-4dc5-b3fa-80ee61ac30ec",
-   "metadata": {},
-   "source": [
-    "## Markdown"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8088840b-ebec-4964-b823-4864330aa021",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "md = Markdown(\"\"\"\n",
-    "### Subtitle\n",
-    "\n",
-    "This is some *markdown* text with math $F=ma$.\n",
-    "\n",
-    "\"\"\")\n",
-    "md"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "de749ce9-0531-4151-b2c5-6100706ddd59",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "display(md)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a4d62188-c67b-4058-a679-a08f6ad0ad87",
-   "metadata": {},
-   "source": [
-    "## LaTeX"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "09eb8496-cea0-496a-97de-f887ce924d3d",
-   "metadata": {},
-   "source": [
-    "Examples LaTeX in a markdown cell:\n",
-    "\n",
-    "\n",
-    "\\begin{align}\n",
-    "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\   \\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
-    "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
-    "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
-    "\\end{align}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e59f7a97-9ad5-424f-ba99-2f69deba04a1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "math = Latex(\"$F=ma$\")\n",
-    "math"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0f14b258-22e0-465d-9b86-d134e7d4a07c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "maxwells = Latex(r\"\"\"\n",
-    "\\begin{align}\n",
-    "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\   \\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
-    "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
-    "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
-    "\\end{align}\n",
-    "\"\"\")\n",
-    "maxwells"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cefadf9b-3bab-451e-963d-38cee15c05ea",
-   "metadata": {},
-   "source": [
-    "## PDF"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0654a20f-1c14-47fd-a8b2-4de3fcbe6379",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "from IPython.display import set_matplotlib_formats\n",
-    "set_matplotlib_formats('pdf')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e472026e-1019-4ef1-aae7-190dfa27c6a6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plt.scatter(np.random.rand(20), np.random.rand(20), c=np.random.rand(20))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "52d8c23c-85e9-4a58-b2ab-a1686f5efaf3",
-   "metadata": {},
-   "source": [
-    "## Image"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e6b7d130-7033-4783-bec1-031beabe66ef",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "img = Image(\"https://apod.nasa.gov/apod/image/1707/GreatWallMilkyWay_Yu_1686.jpg\")\n",
-    "img"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f0063685-9296-4149-abfb-5d0e15cc0b3c",
-   "metadata": {},
-   "source": [
-    "## SVG"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "959bbce1-1bbb-45a4-8373-d3994bab420d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "svg_source = \"\"\"\n",
-    "<svg width=\"400\" height=\"110\">\n",
-    "  <rect width=\"300\" height=\"100\" style=\"fill:#E0E0E0;\" /> \n",
-    "</svg>\n",
-    "\"\"\"\n",
-    "svg = SVG(svg_source)\n",
-    "svg"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "41009292-8e51-4fde-90d2-804a52aa6d7f",
-   "metadata": {},
-   "source": [
-    "## HTML Tables"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dbc0850d-bce6-4b6d-901e-c6ea1b857898",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from vega_datasets import data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "384e0e32-001d-4e40-bda7-4c76578fe123",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = data.cars()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "702d284d-fefb-4b68-a327-ab311179c991",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "5355a073-8ab7-46f9-87c8-04f2a2c4af7c",
-   "metadata": {},
-   "source": [
-    "## Vega"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ba337247-3bfa-4f70-b067-b25d4236660c",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from IPython.display import display\n",
-    "import pandas as pd\n",
-    "\n",
-    "def Vega(spec):\n",
-    "    bundle = {}\n",
-    "    bundle['application/vnd.vega.v5+json'] = spec\n",
-    "    display(bundle, raw=True)\n",
-    "\n",
-    "def VegaLite(spec):\n",
-    "    bundle = {}\n",
-    "    bundle['application/vnd.vegalite.v4+json'] = spec\n",
-    "    display(bundle, raw=True)\n",
-    "\n",
-    "Vega({\n",
-    "  \"$schema\": \"https://vega.github.io/schema/vega/v5.0.json\",\n",
-    "  \"width\": 400,\n",
-    "  \"height\": 200,\n",
-    "  \"padding\": 5,\n",
-    "\n",
-    "  \"data\": [\n",
-    "    {\n",
-    "      \"name\": \"table\",\n",
-    "      \"values\": [\n",
-    "        {\"category\": \"A\", \"amount\": 28},\n",
-    "        {\"category\": \"B\", \"amount\": 55},\n",
-    "        {\"category\": \"C\", \"amount\": 43},\n",
-    "        {\"category\": \"D\", \"amount\": 91},\n",
-    "        {\"category\": \"E\", \"amount\": 81},\n",
-    "        {\"category\": \"F\", \"amount\": 53},\n",
-    "        {\"category\": \"G\", \"amount\": 19},\n",
-    "        {\"category\": \"H\", \"amount\": 87}\n",
-    "      ]\n",
-    "    }\n",
-    "  ],\n",
-    "\n",
-    "  \"signals\": [\n",
-    "    {\n",
-    "      \"name\": \"tooltip\",\n",
-    "      \"value\": {},\n",
-    "      \"on\": [\n",
-    "        {\"events\": \"rect:mouseover\", \"update\": \"datum\"},\n",
-    "        {\"events\": \"rect:mouseout\",  \"update\": \"{}\"}\n",
-    "      ]\n",
-    "    }\n",
-    "  ],\n",
-    "\n",
-    "  \"scales\": [\n",
-    "    {\n",
-    "      \"name\": \"xscale\",\n",
-    "      \"type\": \"band\",\n",
-    "      \"domain\": {\"data\": \"table\", \"field\": \"category\"},\n",
-    "      \"range\": \"width\",\n",
-    "      \"padding\": 0.05,\n",
-    "      \"round\": True\n",
-    "    },\n",
-    "    {\n",
-    "      \"name\": \"yscale\",\n",
-    "      \"domain\": {\"data\": \"table\", \"field\": \"amount\"},\n",
-    "      \"nice\": True,\n",
-    "      \"range\": \"height\"\n",
-    "    }\n",
-    "  ],\n",
-    "\n",
-    "  \"axes\": [\n",
-    "    { \"orient\": \"bottom\", \"scale\": \"xscale\" },\n",
-    "    { \"orient\": \"left\", \"scale\": \"yscale\" }\n",
-    "  ],\n",
-    "\n",
-    "  \"marks\": [\n",
-    "    {\n",
-    "      \"type\": \"rect\",\n",
-    "      \"from\": {\"data\":\"table\"},\n",
-    "      \"encode\": {\n",
-    "        \"enter\": {\n",
-    "          \"x\": {\"scale\": \"xscale\", \"field\": \"category\"},\n",
-    "          \"width\": {\"scale\": \"xscale\", \"band\": 1},\n",
-    "          \"y\": {\"scale\": \"yscale\", \"field\": \"amount\"},\n",
-    "          \"y2\": {\"scale\": \"yscale\", \"value\": 0}\n",
-    "        },\n",
-    "        \"update\": {\n",
-    "          \"fill\": {\"value\": \"steelblue\"}\n",
-    "        },\n",
-    "        \"hover\": {\n",
-    "          \"fill\": {\"value\": \"red\"}\n",
-    "        }\n",
-    "      }\n",
-    "    },\n",
-    "    {\n",
-    "      \"type\": \"text\",\n",
-    "      \"encode\": {\n",
-    "        \"enter\": {\n",
-    "          \"align\": {\"value\": \"center\"},\n",
-    "          \"baseline\": {\"value\": \"bottom\"},\n",
-    "          \"fill\": {\"value\": \"#333\"}\n",
-    "        },\n",
-    "        \"update\": {\n",
-    "          \"x\": {\"scale\": \"xscale\", \"signal\": \"tooltip.category\", \"band\": 0.5},\n",
-    "          \"y\": {\"scale\": \"yscale\", \"signal\": \"tooltip.amount\", \"offset\": -2},\n",
-    "          \"text\": {\"signal\": \"tooltip.amount\"},\n",
-    "          \"fillOpacity\": [\n",
-    "            {\"test\": \"datum === tooltip\", \"value\": 0},\n",
-    "            {\"value\": 1}\n",
-    "          ]\n",
-    "        }\n",
-    "      }\n",
-    "    }\n",
-    "  ]\n",
-    "})"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "be6347a4-f418-49d2-a83e-ba0ef6366505",
-   "metadata": {},
-   "source": [
-    "## GeoJSON"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "67a6bc44-7588-4ae0-8eae-0428b6428f80",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from IPython.display import GeoJSON, JSON\n",
-    "\n",
-    "data = {\n",
-    "    \"type\": \"Feature\",\n",
-    "    \"geometry\": {\n",
-    "        \"type\": \"Point\",\n",
-    "        \"coordinates\": [-118.4563712, 34.0163116]\n",
-    "    }\n",
-    "}\n",
-    "\n",
-    "GeoJSON(data)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1a1a2fc6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "JSON(data)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "dc69fbe1",
-   "metadata": {},
-   "source": [
-    "# Fasta"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "85730759",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def Fasta(data=''):\n",
-    "    bundle = {}\n",
-    "    bundle['application/vnd.fasta.fasta'] = data\n",
-    "    bundle['text/plain'] = data\n",
-    "    display(bundle, raw=True)\n",
-    "\n",
-    "\n",
-    "Fasta(\"\"\">SEQUENCE_1\n",
-    "MTEITAAMVKELRESTGAGMMDCKNALSETNGDFDKAVQLLREKGLGKAAKKADRLAAEG\n",
-    "LVSVKVSDDFTIAAMRPSYLSYEDLDMTFVENEYKALVAELEKENEERRRLKDPNKPEHK\n",
-    "IPQFASRKQLSDAILKEAEEKIKEELKAQGKPEKIWDNIIPGKMNSFIADNSQLDSKLTL\n",
-    "MGQFYVMDDKKTVEQVIAEKEKEFGGKIKIVEFICFEVGEGLEKKTEDFAAEVAAQL\n",
-    ">SEQUENCE_2\n",
-    "SATVSEINSETDFVAKNDQFIALTKDTTAHIQSNSLQSVEELHSSTINGVKFEEYLKSQI\n",
-    "ATIGENLVVRRFATLKAGANGVVNGYIHTNGRVGVVIAAACDSAEVASKSRDLLRQICMH\"\"\")"
-   ]
-  }
- ],
- "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": "3.10.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

notebooks/reveal.ipynb

@@ -1,92 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "print('hi')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import ipywidgets as widgets\n",
-    "slider = widgets.FloatSlider(description='x')\n",
-    "text = widgets.FloatText(disabled=True, description='$x^2$')\n",
-    "text.disabled\n",
-    "def compute(*ignore):\n",
-    "    text.value = str(slider.value**2)\n",
-    "slider.observe(compute, 'value')\n",
-    "slider.value = 14\n",
-    "widgets.VBox([slider, text])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "print('voila')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "slideshow": {
-     "slide_type": "subslide"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "1+2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "celltoolbar": "Slideshow",
-  "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": "3.6.4"
-  },
-  "voila": {
-    "template": "reveal"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}