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Luke Stagner
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add demo notebook
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‎.gitignore

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# PyBuilder
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target/
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# IPython
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.ipynb_checkpoints

‎README.md

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GDL/IDL kernel for Jupyter
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IDL/GDL kernel for Jupyter
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This requires the current development version of IPython 3.0-dev
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To install:
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```sudo python setup.py install```
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This should make an IDL directory containing the kernelspec in the ~/.ipython/kernels directory. If the directory is not made then manually create the directory with the following commands.
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```
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mkdir ~/.ipython/kernels/IDL
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cp kernelspec/kernel.json ~/.ipython/kernels/IDL
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```
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To run:
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```
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ipython console --kernel IDL
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```
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or
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```
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ipython qtconsole --kernel IDL
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```
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or
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```
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ipython notebook
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#Select kernel from dropdown menu
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```
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‎demo.ipynb

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{
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"metadata": {
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"kernelspec": {
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"codemirror_mode": "IDL",
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"display_name": "IDL",
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"language": "IDL",
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"name": "idl"
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},
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"name": "",
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"signature": "sha256:c36a085cd13840f5c7e38f3d752f2d92cd48530483a5a7c8bffa1a2ffbe4354e"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "heading",
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"level": 1,
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"metadata": {},
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"source": [
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"IDL Kernel Demo"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This notebook demostrates the current capability of the IDL IPython/Jupyter Kernel"
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]
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Basic Input & Output"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"a = 1\n",
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"b = 2\n",
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"arr = indgen(5)\n",
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"str = \"Hello, World!\"\n",
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"help,a,b,str,arr"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"A INT = 1\r\n",
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"B INT = 2\r\n",
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"STR STRING = 'Hello, World!'\r\n",
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"ARR INT = Array[5]\r\n"
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]
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}
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],
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"prompt_number": 1
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"print,str"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"Hello, World!\r\n"
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]
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}
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],
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"prompt_number": 2
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Defining Functions & Procedures"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"FUNCTION mysin, x\n",
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" return, sin(x)\n",
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"END"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": []
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}
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],
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"prompt_number": 3
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"print, mysin(2)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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" 0.90930\r\n"
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]
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}
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],
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"prompt_number": 4
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"PRO hello_world\n",
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" print,\"Hello, World!\"\n",
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"END"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": []
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}
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],
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"prompt_number": 5
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"hello_world"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"Hello, World!\r\n"
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]
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}
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],
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"prompt_number": 6
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Inline Plots"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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";;This enables inline plotting\n",
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"!inline=1"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": []
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}
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],
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"prompt_number": 7
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"x = 2*!PI*0.01*indgen(100)\n",
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"y1 = sin(x)\n",
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"y2 = cos(x)\n",
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"loadct,39\n",
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"plot,x,y1,title='Trig Functions',xtitle='Radians',ytitle='Amplitude',xrange=[0,6],charsize=1.5,background=255,color=0\n",
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"oplot,x,y2,color=50"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {
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"png": {
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"height": 384,
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"width": 683
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}
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},
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"output_type": "display_data",
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"png": "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"
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},
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": []
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}
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],
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"prompt_number": 8
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [],
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"language": "python",
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"metadata": {},
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"outputs": []
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}
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],
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"metadata": {}
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}
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]
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}

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