{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Making screenshots programmatically\n", "\n", "Making screenshots on the frontent triggered by `plot.fetch_screenshot()` requires special care.\n", "1. One needs to wait for data before it is synchronized. \n", "2. Before calling `plot.fetch_screenshot()` the plot object must be displayed.\n", "\n", "To change dpi of the image one can use for example: `plot.screenshot_scale = 4.0`.\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import k3d\n", "import numpy as np\n", "from IPython.display import Image\n", "\n", "points_number = 15\n", "spread_range = 30\n", "positions = spread_range * np.random.random_sample((points_number, 3)) - spread_range / 2\n", "colors = np.random.randint(0, 0xFFFFFF, points_number)\n", "\n", "plot = k3d.plot(height=240)\n", "points = k3d.points(positions.astype(np.float32), colors.astype(np.uint32), point_size=3.0, shader='mesh')\n", "plot += points\n", "\n", "plot.display()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Single screenshot\n", "\n", "First, let's generate a single screenshot:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plot.fetch_screenshot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Note**: this operation is asynchronous.\n", "\n", "We need to wait for the widgets to synchronize behind the scenes, before calling the next cell." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "with open('screenshot.png', 'wb') as f:\n", " try:\n", " out = plot.screenshot.decode('base64')\n", " except: # Python 3\n", " from base64 import b64decode\n", " out = b64decode(plot.screenshot) \n", " f.write(out)\n", " \n", "Image(url='screenshot.png')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Multiple screenshots \n", "\n", "\n", "If we want to generate many screenshots within a single cell, it is possible to do it in a following way:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import ipywidgets\n", "\n", "plot.camera_auto_fit = False\n", "plot.grid_auto_fit = False\n", "\n", "speeds = -0.5 * np.sign(positions)\n", "out = ipywidgets.Output()\n", "\n", "@plot.yield_screenshots\n", "def coroutine():\n", " global positions\n", " for i in range(12):\n", " positions += speeds\n", " points.positions = positions.astype(np.float32)\n", " plot.fetch_screenshot()\n", " screenshot = yield\n", " with open('screenshot_%03d.png'%i, 'wb') as f:\n", " f.write(screenshot)\n", " with out:\n", " print('screenshot_%03d.png saved.'%i)\n", " with out:\n", " print('done.')\n", "\n", "coroutine()\n", "print('loop is running in background...')\n", "out" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!convert screenshot_*.png screenshot.gif && rm screenshot_*.png" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Image('screenshot.gif')" ] }, { "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": "3.8.5" }, "nbTranslate": { "displayLangs": [ "en", "pl" ], "hotkey": "alt-t", "langInMainMenu": true, "sourceLang": "pl", "targetLang": "en", "useGoogleTranslate": true }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, "version_major": 2, "version_minor": 0 } } }, "nbformat": 4, "nbformat_minor": 4 }