Docker images to test vispy jupyter notebook backend installation

README.md

This gist holds a docker recipe for testing vispy's jupyter integration. It can be run like:

docker run -p 127.0.0.1:8899:8888 -it --rm mspells/vispy_notebook_tests /bin/bash 
# (setup vispy)
# jupyter notebook --ip 0.0.0.0 --port 8888 --allow-root 

build_image.sh

#!/bin/sh
set -e

OWNER=mspells
PACKAGE=vispy_notebook_tests
TAG=$(date +%Y%m%d)

core_tag="${OWNER}/${PACKAGE}:${TAG}"
latest_tag="${OWNER}/${PACKAGE}:latest"
docker build -f Dockerfile -t "${core_tag}" .
docker tag "${core_tag}" "${latest_tag}"
#docker push "${core_tag}"
#docker push "${latest_tag}"

Dockerfile

FROM ubuntu:latest

RUN apt-get update && apt-get install -y \
    build-essential \
    cython3 \
    git \
    npm \
    python3-fontconfig \
    python3-pip \
    && rm -rf /var/lib/apt/lists/*

RUN apt-get update && apt-get install -y nano && rm -rf /var/lib/apt/lists/* && \
    npm install -g npm@latest && \
    pip3 install --no-cache-dir --upgrade pip setuptools

RUN pip3 install --no-cache-dir jupyter plato-draw && \
    jupyter nbextension enable --py --sys-prefix widgetsnbextension
COPY *.ipynb /

faceted spheres.ipynb

vispy ellipsoids.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import vispy, vispy.app\n",
    "vispy.app.use_app('ipynb_webgl')\n",
    "import plato\n",
    "import plato.draw.vispy as draw\n",
    "import itertools\n",
    "import rowan\n",
    "import numpy as np\n",
    "import IPython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def example_vector_field(N):\n",
    "    xs = np.linspace(-N/2, N/2, N)\n",
    "    positions = np.array(list(itertools.product(xs, xs, xs)), dtype=np.float32)\n",
    "    positions = positions.reshape((-1, 3))\n",
    "\n",
    "    thetas = np.arctan2(positions[:, 1], positions[:, 0])\n",
    "    circle = np.array([-np.sin(thetas), np.cos(thetas), np.zeros_like(thetas)]).T\n",
    "\n",
    "    rotated = np.cross(positions, circle)\n",
    "    rotated /= np.linalg.norm(rotated, axis=-1, keepdims=True)\n",
    "    rotated[np.logical_not(np.all(np.isfinite(rotated), axis=-1))] = (1, 0, 0)\n",
    "\n",
    "    return positions, rotated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = dict(ambient_light=.4)\n",
    "(positions, units) = example_vector_field(5)\n",
    "\n",
    "normalized_z = positions[:, 2].copy()\n",
    "normalized_z -= np.min(normalized_z)\n",
    "normalized_z /= np.max(normalized_z)\n",
    "\n",
    "colors = plato.cmap.cubehelix(normalized_z, h=1.4)\n",
    "colors[:, :3] = .5*(colors[:, :3] +\n",
    "    plato.cmap.cubeellipse(np.arctan2(positions[:, 1], positions[:, 0])))\n",
    "\n",
    "orientations = rowan.vector_vector_rotation([(1, 0, 0)], units)\n",
    "prim = draw.Ellipsoids(\n",
    "    positions=positions, orientations=orientations, colors=colors,\n",
    "    a=.5, b=.125, c=.125)\n",
    "\n",
    "rotation = [ 0.8126942 ,  0.35465172, -0.43531808,  0.15571932]\n",
    "scene = draw.Scene(\n",
    "    prim, zoom=4, features=features, rotation=rotation)\n",
    "scene.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
}