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Animations Using clear_output.ipynb
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/ examples / IPython Kernel / Animations Using clear_output.ipynb
MinRK
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r6463 {
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r18669 "cells": [
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r18669 "cell_type": "markdown",
"metadata": {},
"source": [
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r20547 "# Simple Animations Using clear_output"
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r18669 ]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sometimes you want to clear the output area in the middle of a calculation. This can be useful for doing simple animations. In terminals, there is the carriage-return (`'\\r'`) for overwriting a single line, but the notebook frontend can clear the whole output area, not just a single line.\n",
"\n",
"To clear output in the Notebook you can use the `clear_output()` function. If you are clearing the output every frame of an animation, calling `clear_output()` will create noticeable flickering. You can use `clear_output(wait=True)` to add the *clear_output* call to a queue. When data becomes available to replace the existing output, the *clear_output* will be called immediately before the new data is added. This avoids the flickering by not rendering the cleared output to the screen."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Simple example"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we show our progress iterating through a list:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import sys\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
Brian Granger
More changes to example notebooks.
r9193 {
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r18669 "name": "stdout",
"output_type": "stream",
"text": [
"9\n"
Brian Granger
More changes to example notebooks.
r9193 ]
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r18669 }
],
"source": [
"from IPython.display import display, clear_output\n",
"for i in range(10):\n",
" time.sleep(0.25)\n",
" clear_output(wait=True)\n",
" print(i)\n",
" sys.stdout.flush()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## AsyncResult.wait_interactive"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The AsyncResult object has a special `wait_interactive()` method, which prints its progress interactively,\n",
"so you can watch as your parallel computation completes.\n",
"\n",
"**This example assumes you have an IPython cluster running, which you can start from the [cluster panel](/#clusters)**"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
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r18669 "name": "stdout",
"output_type": "stream",
"text": [
" 100/100 tasks finished after 6 s\n",
"done\n"
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r18669 }
],
"source": [
"from IPython import parallel\n",
"rc = parallel.Client()\n",
"view = rc.load_balanced_view()\n",
"\n",
"amr = view.map_async(time.sleep, [0.5]*100)\n",
"\n",
"amr.wait_interactive()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Matplotlib example"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also use `clear_output()` to clear figures and plots."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
MinRK
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r18669 "data": {
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],
"text/plain": [
"<matplotlib.figure.Figure at 0x10f01b310>"
]
},
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r7739 "metadata": {},
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r18669 "output_type": "display_data"
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r6463 }
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r7739 ],
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r18669 "source": [
"from scipy.special import jn\n",
"x = np.linspace(0,5)\n",
"f, ax = plt.subplots()\n",
"ax.set_title(\"Bessel functions\")\n",
"\n",
"for n in range(1,10):\n",
" time.sleep(1)\n",
" ax.plot(x, jn(x,n))\n",
" clear_output(wait=True)\n",
" display(f)\n",
"\n",
"# close the figure at the end, so we don't get a duplicate\n",
"# of the last plot\n",
"plt.close()"
]
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r6463 }
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r18669 ],
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r20278 "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": "3.4.2"
}
},
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r18669 "nbformat": 4,
"nbformat_minor": 0
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r20278 }