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| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "# GUI\n", | |
| "\n", | |
| "### Jupyter (http://jupyter.org)\n", | |
| "\n", | |
| "Web-based interface for running Julia (which I'm using right now): install locally on your machine\n", | |
| "\n", | |
| "### Juliabox (https://www.juliabox.org)\n", | |
| "\n", | |
| "Free web-based Julia service without installation (Julia may not be up-to-date)\n", | |
| "\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "# About Julia\n", | |
| "\n", | |
| "### Julia (http://julialang.org) \n", | |
| "\n", | |
| "Julia is a new programming language developed from 2009 (public appearance in 2012) by contributers (mostly are from MIT). It is designed for high-performance scientific computing.\n", | |
| "\n", | |
| "It provides an alternative scientific language/platform to Matlab, and very appealing for implementing optimization algorithms:\n", | |
| "0. open and free (MIT license)\n", | |
| "1. well-defined data structure and linear algebra operations,like Matlab\n", | |
| "2. easy to use\n", | |
| "3. support from optimization community, contribute mathematical modeling systems and solvers\n", | |
| "4. Good support for statistics, like R\n", | |
| "5. Easy package system, like R\n", | |
| "\n", | |
| "### The core Julia\n", | |
| "\n", | |
| "The core of Julia is written in C/C++ with parsers in Scheme and JIT compilation in the LLVM compiler framework. Most of julia libraries are written in Julia itself. \n", | |
| "\n", | |
| "<!-- Some distinctive language features include:\n", | |
| "* dynamic and strong type system\n", | |
| "* multiple dispatch: Julia is function-based where the behavior of a function can be defined for multiple combinations of argument types\n", | |
| "* macro system: Lisp-like\n", | |
| "* integration: Python by the PyCall package, call C functions directly\n", | |
| "* Jupyter (previously IJulia): interactive web-based interface similar to Mathematica\n", | |
| "* JIT: fast performance\n", | |
| "* Support for unicode: even for variable names!\n", | |
| "* Git-based built-in package system: Pkg.add(\"mypackage\"), using mypackage, ...\n", | |
| "-->\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "\n", | |
| "# Learn by examples" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Julia Version 0.4.5\n", | |
| "Commit 2ac304d (2016-03-18 00:58 UTC)\n", | |
| "Platform Info:\n", | |
| " System: Darwin (x86_64-apple-darwin13.4.0)\n", | |
| " CPU: Intel(R) Core(TM) i7-4650U CPU @ 1.70GHz\n", | |
| " WORD_SIZE: 64\n", | |
| " BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)\n", | |
| " LAPACK: libopenblas64_\n", | |
| " LIBM: libopenlibm\n", | |
| " LLVM: libLLVM-3.3\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "versioninfo()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Hello World" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Hello Julia\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "println(\"Hello Julia\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "search: print println print_joined print_escaped print_shortest print_unescaped\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "text/latex": [ | |
| "\\begin{verbatim}\n", | |
| "print(x)\n", | |
| "\\end{verbatim}\n", | |
| "Write (to the default output stream) a canonical (un-decorated) text representation of a value if there is one, otherwise call \\texttt{show}. The representation used by \\texttt{print} includes minimal formatting and tries to avoid Julia-specific details.\n" | |
| ], | |
| "text/markdown": [ | |
| "```\n", | |
| "print(x)\n", | |
| "```\n", | |
| "\n", | |
| "Write (to the default output stream) a canonical (un-decorated) text representation of a value if there is one, otherwise call `show`. The representation used by `print` includes minimal formatting and tries to avoid Julia-specific details.\n" | |
| ], | |
| "text/plain": [ | |
| "```\n", | |
| "print(x)\n", | |
| "```\n", | |
| "\n", | |
| "Write (to the default output stream) a canonical (un-decorated) text representation of a value if there is one, otherwise call `show`. The representation used by `print` includes minimal formatting and tries to avoid Julia-specific details.\n" | |
| ] | |
| }, | |
| "execution_count": 6, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "?print" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Variable Types" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 98, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Int64" | |
| ] | |
| }, | |
| "execution_count": 98, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = 3\n", | |
| "typeof(a)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "ASCIIString" | |
| ] | |
| }, | |
| "execution_count": 8, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = \"a string\"\n", | |
| "typeof(a)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Float64" | |
| ] | |
| }, | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = 1e-7\n", | |
| "typeof(a)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Logicals" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "true" | |
| ] | |
| }, | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "1 == true" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "true" | |
| ] | |
| }, | |
| "execution_count": 11, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "0 == false" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "false" | |
| ] | |
| }, | |
| "execution_count": 12, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "!true" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 99, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "negative\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "a = -1\n", | |
| "if a>0 \n", | |
| " println(\"positive\")\n", | |
| "elseif a<0\n", | |
| " println(\"negative\")\n", | |
| "else\n", | |
| " println(\"zero\")\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 14, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "ename": "LoadError", | |
| "evalue": "LoadError: TypeError: non-boolean (Int64) used in boolean context\nwhile loading In[14], in expression starting on line 1", | |
| "output_type": "error", | |
| "traceback": [ | |
| "LoadError: TypeError: non-boolean (Int64) used in boolean context\nwhile loading In[14], in expression starting on line 1", | |
| "" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "if 1 \n", | |
| " println(\"true\")\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Functions" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 15, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "sphere_vol (generic function with 1 method)" | |
| ] | |
| }, | |
| "execution_count": 15, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "function sphere_vol(r)\n", | |
| " return 4/3*pi*r^3\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 16, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "sphere_vol (generic function with 1 method)" | |
| ] | |
| }, | |
| "execution_count": 16, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "function sphere_vol(r)\n", | |
| " 4/3*pi*r^3\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 17, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "sphere radius=5.000000, vol=523.599\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "r = 5\n", | |
| "# print(\"sphere radius=%f, vol=%0.3f\\n\", r, sphere_vol(r))\n", | |
| "@printf \"sphere radius=%f, vol=%0.3f\\n\" r sphere_vol(r)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 18, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1.2246467991473532e-16" | |
| ] | |
| }, | |
| "execution_count": 18, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "f(x) = sin(1 / x)\n", | |
| "f(1/pi)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 19, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "quad_root (generic function with 1 method)" | |
| ] | |
| }, | |
| "execution_count": 19, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "quad_root(a,b,c) = ((-b + sqrt(b^2-4a*c))/2a, (-b - sqrt(b^2-4a*c))/2a)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 20, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "(-0.2928932188134524,-1.7071067811865475)" | |
| ] | |
| }, | |
| "execution_count": 20, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "soln = quad_root(2,4,1)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 21, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "-0.2928932188134524" | |
| ] | |
| }, | |
| "execution_count": 21, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "soln[1]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 22, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "ename": "LoadError", | |
| "evalue": "LoadError: MethodError: `getindex` has no method matching getindex(::Tuple{Float64,Float64}, ::Colon)\nClosest candidates are:\n getindex(::Tuple, !Matched::Int64)\n getindex(::Tuple, !Matched::Real)\n getindex(::Tuple, !Matched::AbstractArray{Bool,N})\n ...\nwhile loading In[22], in expression starting on line 2", | |
| "output_type": "error", | |
| "traceback": [ | |
| "LoadError: MethodError: `getindex` has no method matching getindex(::Tuple{Float64,Float64}, ::Colon)\nClosest candidates are:\n getindex(::Tuple, !Matched::Int64)\n getindex(::Tuple, !Matched::Real)\n getindex(::Tuple, !Matched::AbstractArray{Bool,N})\n ...\nwhile loading In[22], in expression starting on line 2", | |
| "" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "\n", | |
| "soln[:]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 23, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3-element Array{Float64,1}:\n", | |
| " 0.721004\n", | |
| " 0.251543\n", | |
| " 0.841597" | |
| ] | |
| }, | |
| "execution_count": 23, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "map(x -> sin(1 / x), randn(3)) # function without a name, apply a function on the elements of an array" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 24, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "f (generic function with 3 methods)" | |
| ] | |
| }, | |
| "execution_count": 24, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "function f(x, y=2, z=3; a=1, b=.1, c=2) # default values, named arguments\n", | |
| " return exp(cos(a * x + b))\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 25, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "2.718281828459045" | |
| ] | |
| }, | |
| "execution_count": 25, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "f(1, 2, 3, b=-1)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Print " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 97, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "ename": "LoadError", | |
| "evalue": "LoadError: invalid redefinition of constant f\nwhile loading In[97], in expression starting on line 2", | |
| "output_type": "error", | |
| "traceback": [ | |
| "LoadError: invalid redefinition of constant f\nwhile loading In[97], in expression starting on line 2", | |
| "" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "s = \"3.1415\"\n", | |
| "f=0\n", | |
| "gc()\n", | |
| "\n", | |
| "f = float(s) \n", | |
| "println(5f)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 27, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "ename": "LoadError", | |
| "evalue": "LoadError: ArgumentError: invalid base 10 digit '.' in \"3.1415\"\nwhile loading In[27], in expression starting on line 1", | |
| "output_type": "error", | |
| "traceback": [ | |
| "LoadError: ArgumentError: invalid base 10 digit '.' in \"3.1415\"\nwhile loading In[27], in expression starting on line 1", | |
| "", | |
| " in tryparse_internal at /Applications/Julia-0.4.5.app/Contents/Resources/julia/lib/julia/sys.dylib (repeats 2 times)", | |
| " in parse at /Applications/Julia-0.4.5.app/Contents/Resources/julia/lib/julia/sys.dylib" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "i = parse(Int,s)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 28, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "α, ascii value = 945\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "c = 'α'\n", | |
| "println(c, \", ascii value = \", Int(c))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 29, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "\"s i\"" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "str = \"This is a string\"\n", | |
| "show(str[4:6])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 30, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "welcome to julia in 1\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "a = \"welcome\"\n", | |
| "b = \"julia\"\n", | |
| "c = 1\n", | |
| "println(\"$a to $b in $c\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 31, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "1 + 2 = 3\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "println(\"1 + 2 = $(1+2)\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Strings" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 32, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "welcomejulia\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "a = \"welcome\"\n", | |
| "b = \"julia\"\n", | |
| "println(a * b) # string concatenation" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 33, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "\"welcomewelcomewelcome\"" | |
| ] | |
| }, | |
| "execution_count": 33, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a^3" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 34, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "11:15" | |
| ] | |
| }, | |
| "execution_count": 34, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "s = \"The quick brown fox jumps over the lazy dog α,β,γ \"\n", | |
| "r = search(s, \"brown\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 35, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "\"The quick red fox jumps over the lazy dog α,β,γ \"" | |
| ] | |
| }, | |
| "execution_count": 35, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "r = replace(s, \"brown\", \"red\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 36, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "11:15" | |
| ] | |
| }, | |
| "execution_count": 36, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "r = search(s, r\"b[\\w]*n\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 37, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "\"The quick brown fox jumps over the lazy dog α,β,γ\"" | |
| ] | |
| }, | |
| "execution_count": 37, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "r = strip(s)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 38, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3-element Array{SubString{ASCIIString},1}:\n", | |
| " \"welcome\"\n", | |
| " \"to\" \n", | |
| " \"julia\" " | |
| ] | |
| }, | |
| "execution_count": 38, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "r = split(\"welcome, to, julia\", [',', ' '], limit=0, keep=false)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 39, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "### Arrays" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 40, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1x3 Array{Int64,2}:\n", | |
| " 1 2 3" | |
| ] | |
| }, | |
| "execution_count": 40, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = [1 2 3]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 41, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3-element Array{Int64,1}:\n", | |
| " 1\n", | |
| " 2\n", | |
| " 3" | |
| ] | |
| }, | |
| "execution_count": 41, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = [1,2,3]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 42, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3-element Array{Int64,1}:\n", | |
| " 1\n", | |
| " 2\n", | |
| " 3" | |
| ] | |
| }, | |
| "execution_count": 42, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = [1;2;3]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 43, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "[4,5,6]\n", | |
| "[4,5,6]" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "a = Int64[]\n", | |
| "push!(a, 4)\n", | |
| "push!(a, 5)\n", | |
| "tmp = push!(a,6)\n", | |
| "show(tmp); println()\n", | |
| "show(a)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 44, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "2-element Array{Array{Int64,1},1}:\n", | |
| " [1,2,3]\n", | |
| " [4,5] " | |
| ] | |
| }, | |
| "execution_count": 44, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = (Array{Int64, 1})[] # Array of Arrays\n", | |
| "push!(a, [1,2,3])\n", | |
| "push!(a, [4,5])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 45, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3x6 Array{Int64,2}:\n", | |
| " 1 2 3 1 2 3\n", | |
| " 1 2 3 1 2 3\n", | |
| " 1 2 3 1 2 3" | |
| ] | |
| }, | |
| "execution_count": 45, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = [1 2 3]\n", | |
| "A = repmat(a, 3, 2)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 46, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "2x3 Array{ByteString,2}:\n", | |
| " \"Hi Im element # 1\" \"Hi Im element # 3\" \"Hi Im element # 5\"\n", | |
| " \"Hi Im element # 2\" \"Hi Im element # 4\" \"Hi Im element # 6\"" | |
| ] | |
| }, | |
| "execution_count": 46, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = [\"Hi Im element # $(i+2*(j-1))\" for i=1:2, j=1:3]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 47, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "2-element Array{ByteString,1}:\n", | |
| " \"Hi Im element # 3\"\n", | |
| " \"Hi Im element # 4\"" | |
| ] | |
| }, | |
| "execution_count": 47, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a[:,2]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 48, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1x3 Array{ByteString,2}:\n", | |
| " \"Hi Im element # 2\" \"Hi Im element # 4\" \"Hi Im element # 6\"" | |
| ] | |
| }, | |
| "execution_count": 48, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a[end,:]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 49, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "6-element Array{Int64,1}:\n", | |
| " 1\n", | |
| " 2\n", | |
| " 3\n", | |
| " 4\n", | |
| " 5\n", | |
| " 6" | |
| ] | |
| }, | |
| "execution_count": 49, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "push!([1,2,3], 4, 5, 6)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 50, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "6-element Array{Int64,1}:\n", | |
| " 1\n", | |
| " 2\n", | |
| " 3\n", | |
| " 4\n", | |
| " 5\n", | |
| " 6" | |
| ] | |
| }, | |
| "execution_count": 50, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "append!([1,2,3], [4,5,6])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 51, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3-element Array{Int64,1}:\n", | |
| " 1\n", | |
| " 2\n", | |
| " 3" | |
| ] | |
| }, | |
| "execution_count": 51, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "prepend!([3], [1,2])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 52, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "5-element Array{Int64,1}:\n", | |
| " 1\n", | |
| " 10\n", | |
| " 2\n", | |
| " 3\n", | |
| " 4" | |
| ] | |
| }, | |
| "execution_count": 52, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "insert!([1,2,3,4],2,10)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 53, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "2-element Array{Int64,1}:\n", | |
| " 1\n", | |
| " 4" | |
| ] | |
| }, | |
| "execution_count": 53, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "deleteat!([1,2,3,4],2:3)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Call by Reference" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 54, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "10" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "function foo(arg::Int)\n", | |
| " arg_local = arg\n", | |
| " arg_local = 2\n", | |
| " return (arg_local)\n", | |
| "end\n", | |
| "\n", | |
| "arg = 10\n", | |
| "foo(arg)\n", | |
| "show(arg)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 55, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "ename": "LoadError", | |
| "evalue": "LoadError: MethodError: `isless` has no method matching isless(::Array{Int64,2}, ::Int64)\nClosest candidates are:\n isless(!Matched::AbstractFloat, ::Real)\n isless(!Matched::Real, ::Real)\n isless(!Matched::Char, ::Integer)\n ...\nwhile loading In[55], in expression starting on line 8", | |
| "output_type": "error", | |
| "traceback": [ | |
| "LoadError: MethodError: `isless` has no method matching isless(::Array{Int64,2}, ::Int64)\nClosest candidates are:\n isless(!Matched::AbstractFloat, ::Real)\n isless(!Matched::Real, ::Real)\n isless(!Matched::Char, ::Integer)\n ...\nwhile loading In[55], in expression starting on line 8", | |
| "" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "function foo!(arg::Array)\n", | |
| " arg_local = arg\n", | |
| " arg_local[1] = 2\n", | |
| " return (arg_local)\n", | |
| "end\n", | |
| "\n", | |
| "arg = [10 20]\n", | |
| "foo(arg)\n", | |
| "show(arg)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 56, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3x3 Array{Float64,2}:\n", | |
| " 1.0 1.0 1.0\n", | |
| " 1.0 1.0 1.0\n", | |
| " 1.0 1.0 1.0" | |
| ] | |
| }, | |
| "execution_count": 56, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "A = ones(3,3)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 57, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3x3 Array{Float64,2}:\n", | |
| " 1.0 1.0 1.0\n", | |
| " 1.0 -1.0 1.0\n", | |
| " 1.0 1.0 1.0" | |
| ] | |
| }, | |
| "execution_count": 57, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "B = A\n", | |
| "A[2,2] = -1\n", | |
| "B" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 58, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3x3 Array{Float64,2}:\n", | |
| " 1.0 1.0 1.0\n", | |
| " 1.0 -1.0 1.0\n", | |
| " 1.0 1.0 1.0" | |
| ] | |
| }, | |
| "execution_count": 58, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "B = copy(A)\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "raw", | |
| "metadata": {}, | |
| "source": [ | |
| "More about arrays, see (http://quant-econ.net/jl/julia_arrays.html)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Tuples " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 59, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Tuple{ASCIIString,ASCIIString}" | |
| ] | |
| }, | |
| "execution_count": 59, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "x = (\"foo\", \"bar\")\n", | |
| "typeof(x)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 60, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "\"foo\"\n", | |
| "\"bar\"" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "x = \"foo\", \"bar\"\n", | |
| "word1, word2 = x # unpacking\n", | |
| "show(word1); println()\n", | |
| "show(word2)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 61, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "\"foo\"" | |
| ] | |
| }, | |
| "execution_count": 61, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "x = (\"foo\", \"bar\")\n", | |
| "x[1]\n", | |
| "#x[1] = \"xxx\"\n", | |
| "#show(x)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 62, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "ASCIIString[\"xxx\" \"bar\"]" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "x = [\"foo\" \"bar\"]\n", | |
| "x[1] = \"xxx\"\n", | |
| "show(x)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Dictionary" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 63, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Dict{Any,Any} with 4 entries:\n", | |
| " 4 => \"four\"\n", | |
| " 2 => \"two\"\n", | |
| " 3 => \"three\"\n", | |
| " 1 => \"one\"" | |
| ] | |
| }, | |
| "execution_count": 63, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "d = Dict{Any,Any}(2=>\"two\", 1=>\"one\", 4=>\"four\", 3=>\"three\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 64, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Dict{Int64,ASCIIString} with 4 entries:\n", | |
| " 4 => \"four\"\n", | |
| " 2 => \"two\"\n", | |
| " 3 => \"three\"\n", | |
| " 1 => \"one\"" | |
| ] | |
| }, | |
| "execution_count": 64, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# alternatively,\n", | |
| "d = Dict(2=>\"two\", 1=>\"one\", 4=>\"four\", 3=>\"three\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 65, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "[4,2,3,1]\n", | |
| "ASCIIString[\"four\",\"two\",\"three\",\"one\"]" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "show(keys(d)); println()\n", | |
| "show(values(d))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 66, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "2: two, 3: three, " | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "for k in sort(collect(keys(d)))\n", | |
| " if(k == 1) continue\n", | |
| " end\n", | |
| " if(k == 4) break\n", | |
| " end\n", | |
| " print(k, \": \", d[k], \", \")\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 67, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "\"three\"\"not three\"" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "show(d[3])\n", | |
| "d[3] = \"not three\"\n", | |
| "show(d[3])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 68, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "\"zero\"" | |
| ] | |
| }, | |
| "execution_count": 68, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "d[0] = \"zero\"" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 69, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Dict(0=>\"zero\",4=>\"four\",2=>\"two\",3=>\"not three\",1=>\"one\")" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "true" | |
| ] | |
| }, | |
| "execution_count": 69, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "show(d)\n", | |
| "1 in keys(d)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 70, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "true" | |
| ] | |
| }, | |
| "execution_count": 70, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "\"one\" in values(d)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Comprehension" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 71, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3-element Array{ByteString,1}:\n", | |
| " \"dogs\" \n", | |
| " \"cats\" \n", | |
| " \"birds\"" | |
| ] | |
| }, | |
| "execution_count": 71, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "animals = [\"dog\", \"cat\", \"bird\"]; # semicolon suppresses output\n", | |
| "\n", | |
| "plurals = [animal * \"s\" for animal in animals]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 72, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "2x3 Array{Int64,2}:\n", | |
| " 2 3 4\n", | |
| " 3 4 5" | |
| ] | |
| }, | |
| "execution_count": 72, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "a = [i+j for i=1:2, j=1:3]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 73, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Dict{ASCIIString,Int64} with 3 entries:\n", | |
| " \"1\" => 1\n", | |
| " \"2\" => 2\n", | |
| " \"3\" => 3" | |
| ] | |
| }, | |
| "execution_count": 73, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "[\"$i\" => i for i in 1:3]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 74, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Dict{Int64,ByteString} with 10 entries:\n", | |
| " 7 => \"str7\"\n", | |
| " 4 => \"str4\"\n", | |
| " 9 => \"str9\"\n", | |
| " 10 => \"str10\"\n", | |
| " 2 => \"str2\"\n", | |
| " 3 => \"str3\"\n", | |
| " 5 => \"str5\"\n", | |
| " 8 => \"str8\"\n", | |
| " 6 => \"str6\"\n", | |
| " 1 => \"str1\"" | |
| ] | |
| }, | |
| "execution_count": 74, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "d = [i => @sprintf(\"str%d\", i) for i=1:10]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Loops" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 75, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "1, 2, 3, 4, 5, " | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "for i in 1:5 # iteration over a range 1:5, \"for i = 1:5\" also works\n", | |
| " print(i, \", \")\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 76, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "1, 2, 3, 4, 5, " | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "for i in collect(1:5) # iteration over an array\n", | |
| " print(i, \", \")\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 77, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "9, 7, 5, 3, 1, " | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "a = collect(1:2:10)\n", | |
| "while !isempty(a)\n", | |
| " print(pop!(a), \", \")\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 78, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "The capital of Japan is Tokyo\n", | |
| "The capital of Korea is Seoul\n", | |
| "The capital of China is Beijing\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "countries = (\"Japan\", \"Korea\", \"China\")\n", | |
| "cities = (\"Tokyo\", \"Seoul\", \"Beijing\")\n", | |
| "for (country, city) in zip(countries, cities) # zip()\n", | |
| " println(\"The capital of $country is $city\")\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 79, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "The capital of Japan is Tokyo\n", | |
| "The capital of Korea is Seoul\n", | |
| "The capital of China is Beijing\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "countries = (\"Japan\", \"Korea\", \"China\")\n", | |
| "cities = (\"Tokyo\", \"Seoul\", \"Beijing\")\n", | |
| "for (i, country) in enumerate(countries) # above example, with index\n", | |
| " city = cities[i]\n", | |
| " println(\"The capital of $country is $city\")\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Custom Types" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 80, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Person(\"Julia\",4.0,AbstractString[])\n", | |
| "Person(\"Steve\",42.0,AbstractString[\"Anna\",\"Bob\"])" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "type Person\n", | |
| " name::AbstractString\n", | |
| " age::Float64\n", | |
| " children::Array{AbstractString, 1}\n", | |
| " \n", | |
| " # constructor\n", | |
| " Person(name::AbstractString, age) = new(name, age, [])\n", | |
| " Person(name::AbstractString, age, children) = new(name, age, children)\n", | |
| "end\n", | |
| "\n", | |
| "p1 = Person(\"Julia\", 4)\n", | |
| "p2 = Person(\"Steve\", 42, [\"Anna\", \"Bob\"])\n", | |
| "show(p1); println()\n", | |
| "show(p2)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 81, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1-element Array{Person,1}:\n", | |
| " Person(\"Steve\",42.0,AbstractString[])" | |
| ] | |
| }, | |
| "execution_count": 81, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "people = Person[]\n", | |
| "push!(people, Person(\"Steve\", 42))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### File Input" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 82, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "c,fib,0.046968\n", | |
| "c,mandel,0.406981\n", | |
| "c,parse_int,0.187874\n", | |
| "c,pi_sum,46.528101\n", | |
| "c,printfd,22.814035\n", | |
| "c,quicksort,0.516176\n", | |
| "c,rand_mat_mul,236.536026\n", | |
| "c,rand_mat_stat,11.954784\n", | |
| "fortran,fib,.032889\n", | |
| "fortran,mandel,.299340\n", | |
| "fortran,parse_int,.917261\n", | |
| "fortran,pi_sum,46.140000\n", | |
| "fortran,quicksort,.676291\n", | |
| "fortran,rand_mat_mul,1119.072000\n", | |
| "fortran,rand_mat_stat,13.744000\n", | |
| "go,fib,0.10060900000000002\n", | |
| "go,mandel,0.404544\n", | |
| "go,parse_int,0.708133\n", | |
| "go,pi_sum,61.80803100000001\n", | |
| "go,quicksort,0.5738630000000001\n", | |
| "go,rand_mat_mul,2325.240173\n", | |
| "go,rand_mat_stat,106.68269000000001\n", | |
| "java,fib,0.042393\n", | |
| "java,mandel,0.231601\n", | |
| "java,parse_int,1.043216\n", | |
| "java,pi_sum,46.616215\n", | |
| "java,printfd,119.493350\n", | |
| "java,quicksort,0.871698\n", | |
| "java,rand_mat_mul,555.709576\n", | |
| "java,rand_mat_stat,47.901065\n", | |
| "java,sinc_sum,0.155235\n", | |
| "javascript,fib,0.175\n", | |
| "javascript,mandel,0.632\n", | |
| "javascript,parse_int,0.438\n", | |
| "javascript,pi_sum,102.1\n", | |
| "javascript,quicksort,1.5\n", | |
| "javascript,rand_mat_mul,4067\n", | |
| "javascript,rand_mat_stat,39.7\n", | |
| "julia,fib,0.112414\n", | |
| "julia,mandel,0.293425\n", | |
| "julia,parse_int,0.362631\n", | |
| "julia,pi_sum,49.372756\n", | |
| "julia,printfd,45.527162\n", | |
| "julia,quicksort,0.640893\n", | |
| "julia,rand_mat_mul,261.875685\n", | |
| "julia,rand_mat_stat,25.633835\n", | |
| "lua,fib,0.112\n", | |
| "lua,mandel,0.287\n", | |
| "lua,parse_int,1.276\n", | |
| "lua,pi_sum,55.045\n", | |
| "lua,quicksort,1.217\n", | |
| "lua,rand_mat_mul,339.773\n", | |
| "lua,rand_mat_stat,51.834\n", | |
| "mathematica,fib,7.676\n", | |
| "mathematica,mandel,2.54\n", | |
| "mathematica,parse_int,3.317\n", | |
| "mathematica,pi_sum,70.181\n", | |
| "mathematica,quicksort,24.885\n", | |
| "mathematica,rand_mat_mul,285.801\n", | |
| "mathematica,rand_mat_stat,80.199\n", | |
| "matlab,fib,217.85100000\n", | |
| "matlab,mandel,20.84800000\n", | |
| "matlab,parse_int,296.93900000\n", | |
| "matlab,pi_sum,59.23900000\n", | |
| "matlab,printfd,2446.41600000\n", | |
| "matlab,quicksort,28.09500000\n", | |
| "matlab,rand_mat_mul,279.38000000\n", | |
| "matlab,rand_mat_stat,125.26700000\n", | |
| "octave,fib,458.62197876\n", | |
| "octave,mandel,159.23213959\n", | |
| "octave,parse_int,1710.93678474\n", | |
| "octave,pi_sum,13005.94305992\n", | |
| "octave,printfd,2002.40898132\n", | |
| "octave,quicksort,911.63611412\n", | |
| "octave,rand_mat_mul,295.38583755\n", | |
| "octave,rand_mat_stat,429.40402031\n", | |
| "python,fib,3.75509262085\n", | |
| "python,mandel,4.958152771\n", | |
| "python,parse_int,2.30002403259\n", | |
| "python,pi_sum,787.712097168\n", | |
| "python,quicksort,17.1549320221\n", | |
| "python,rand_mat_mul,294.181108475\n", | |
| "python,rand_mat_stat,227.633953094\n", | |
| "r,fib,26.00000000\n", | |
| "r,mandel,22.00000000\n", | |
| "r,parse_int,10.00000000\n", | |
| "r,pi_sum,770.00000000\n", | |
| "r,quicksort,132.00000000\n", | |
| "r,rand_mat_mul,452.00000000\n", | |
| "r,rand_mat_stat,199.00000000\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "fname = \"benchmarks.csv\"\n", | |
| "\n", | |
| "open(fname, \"r\") do f\n", | |
| " for line in eachline(f)\n", | |
| " print(line)\n", | |
| " end\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 83, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "ename": "LoadError", | |
| "evalue": "LoadError: invalid redefinition of constant f\nwhile loading In[83], in expression starting on line 1", | |
| "output_type": "error", | |
| "traceback": [ | |
| "LoadError: invalid redefinition of constant f\nwhile loading In[83], in expression starting on line 1", | |
| "" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "f = open(fname, \"r\")\n", | |
| "showall(readlines(f))\n", | |
| "close(f)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Plotting" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 100, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "using DataFrames\n", | |
| "using Gadfly # ggplot2 style plots\n", | |
| "\n", | |
| "benchmarks = readtable(\"benchmarks.csv\", names=[:language, :benchmark, :time])\n", | |
| "# show(benchmarks)\n", | |
| "cdata = benchmarks[benchmarks[:language].== \"c\", :]\n", | |
| "# show(cdata)\n", | |
| "benchmarks = join(benchmarks, cdata, on=:benchmark)\n", | |
| "# show(benchmarks)\n", | |
| "benchmarks[:time]./= benchmarks[:time_1]\n", | |
| "#benchmarks[:language] = PooledDataArray(benchmarks[:language])\n", | |
| "#benchmarks[:benchmark] = PooledDataArray(benchmarks[:benchmark])\n", | |
| "benchmarks = benchmarks[benchmarks[:language].!= \"c\", :]\n", | |
| "#benchmarks[:language] = setlevels!(benchmarks[:language], Dict{UTF8String,Any}(benchmarks[:language],\n", | |
| "# [ lang == \"javascript\" ? \"JavaScript\" : ucfirst(lang) for lang in benchmarks[:language]]));" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 85, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<table class=\"data-frame\"><tr><th></th><th>language</th><th>benchmark</th><th>time</th><th>language_1</th><th>time_1</th></tr><tr><th>1</th><td>fortran</td><td>mandel</td><td>0.7355134514879074</td><td>c</td><td>0.406981</td></tr><tr><th>2</th><td>go</td><td>mandel</td><td>0.9940120054744571</td><td>c</td><td>0.406981</td></tr><tr><th>3</th><td>java</td><td>mandel</td><td>0.569070792002575</td><td>c</td><td>0.406981</td></tr><tr><th>4</th><td>javascript</td><td>mandel</td><td>1.5528980468375675</td><td>c</td><td>0.406981</td></tr><tr><th>5</th><td>julia</td><td>mandel</td><td>0.7209796034704323</td><td>c</td><td>0.406981</td></tr><tr><th>6</th><td>lua</td><td>mandel</td><td>0.7051926256999712</td><td>c</td><td>0.406981</td></tr><tr><th>7</th><td>mathematica</td><td>mandel</td><td>6.241077593302882</td><td>c</td><td>0.406981</td></tr><tr><th>8</th><td>matlab</td><td>mandel</td><td>51.22597860833798</td><td>c</td><td>0.406981</td></tr><tr><th>9</th><td>octave</td><td>mandel</td><td>391.25202304284477</td><td>c</td><td>0.406981</td></tr><tr><th>10</th><td>python</td><td>mandel</td><td>12.182762269000273</td><td>c</td><td>0.406981</td></tr><tr><th>11</th><td>r</td><td>mandel</td><td>54.05657757978874</td><td>c</td><td>0.406981</td></tr><tr><th>12</th><td>fortran</td><td>parse_int</td><td>4.882320065575865</td><td>c</td><td>0.187874</td></tr><tr><th>13</th><td>go</td><td>parse_int</td><td>3.769191053578462</td><td>c</td><td>0.187874</td></tr><tr><th>14</th><td>java</td><td>parse_int</td><td>5.5527427957035025</td><td>c</td><td>0.187874</td></tr><tr><th>15</th><td>javascript</td><td>parse_int</td><td>2.331349734396457</td><td>c</td><td>0.187874</td></tr><tr><th>16</th><td>julia</td><td>parse_int</td><td>1.9301819304427432</td><td>c</td><td>0.187874</td></tr><tr><th>17</th><td>lua</td><td>parse_int</td><td>6.791785984223469</td><td>c</td><td>0.187874</td></tr><tr><th>18</th><td>mathematica</td><td>parse_int</td><td>17.655449929207872</td><td>c</td><td>0.187874</td></tr><tr><th>19</th><td>matlab</td><td>parse_int</td><td>1580.5220520135836</td><td>c</td><td>0.187874</td></tr><tr><th>20</th><td>octave</td><td>parse_int</td><td>9106.831092860108</td><td>c</td><td>0.187874</td></tr><tr><th>21</th><td>python</td><td>parse_int</td><td>12.242375382383937</td><td>c</td><td>0.187874</td></tr><tr><th>22</th><td>r</td><td>parse_int</td><td>53.22716288576386</td><td>c</td><td>0.187874</td></tr><tr><th>23</th><td>fortran</td><td>pi_sum</td><td>0.9916587827214354</td><td>c</td><td>46.528101</td></tr><tr><th>24</th><td>go</td><td>pi_sum</td><td>1.3284021843057814</td><td>c</td><td>46.528101</td></tr><tr><th>25</th><td>java</td><td>pi_sum</td><td>1.0018937802769985</td><td>c</td><td>46.528101</td></tr><tr><th>26</th><td>javascript</td><td>pi_sum</td><td>2.1943728156883084</td><td>c</td><td>46.528101</td></tr><tr><th>27</th><td>julia</td><td>pi_sum</td><td>1.0611384290108896</td><td>c</td><td>46.528101</td></tr><tr><th>28</th><td>lua</td><td>pi_sum</td><td>1.1830484979389122</td><td>c</td><td>46.528101</td></tr><tr><th>29</th><td>mathematica</td><td>pi_sum</td><td>1.5083572828386012</td><td>c</td><td>46.528101</td></tr><tr><th>30</th><td>matlab</td><td>pi_sum</td><td>1.2731875732474016</td><td>c</td><td>46.528101</td></tr><tr><th>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr></table>" | |
| ], | |
| "text/plain": [ | |
| "70x5 DataFrames.DataFrame\n", | |
| "│ Row │ language │ benchmark │ time │ language_1 │ time_1 │\n", | |
| "┝━━━━━┿━━━━━━━━━━━━━━━┿━━━━━━━━━━━━━━━━━┿━━━━━━━━━━┿━━━━━━━━━━━━┿━━━━━━━━━━┥\n", | |
| "│ 1 │ \"fortran\" │ \"mandel\" │ 0.735513 │ \"c\" │ 0.406981 │\n", | |
| "│ 2 │ \"go\" │ \"mandel\" │ 0.994012 │ \"c\" │ 0.406981 │\n", | |
| "│ 3 │ \"java\" │ \"mandel\" │ 0.569071 │ \"c\" │ 0.406981 │\n", | |
| "│ 4 │ \"javascript\" │ \"mandel\" │ 1.5529 │ \"c\" │ 0.406981 │\n", | |
| "│ 5 │ \"julia\" │ \"mandel\" │ 0.72098 │ \"c\" │ 0.406981 │\n", | |
| "│ 6 │ \"lua\" │ \"mandel\" │ 0.705193 │ \"c\" │ 0.406981 │\n", | |
| "│ 7 │ \"mathematica\" │ \"mandel\" │ 6.24108 │ \"c\" │ 0.406981 │\n", | |
| "│ 8 │ \"matlab\" │ \"mandel\" │ 51.226 │ \"c\" │ 0.406981 │\n", | |
| "│ 9 │ \"octave\" │ \"mandel\" │ 391.252 │ \"c\" │ 0.406981 │\n", | |
| "│ 10 │ \"python\" │ \"mandel\" │ 12.1828 │ \"c\" │ 0.406981 │\n", | |
| "│ 11 │ \"r\" │ \"mandel\" │ 54.0566 │ \"c\" │ 0.406981 │\n", | |
| "⋮\n", | |
| "│ 59 │ \"r\" │ \"rand_mat_mul\" │ 1.91091 │ \"c\" │ 236.536 │\n", | |
| "│ 60 │ \"fortran\" │ \"rand_mat_stat\" │ 1.14967 │ \"c\" │ 11.9548 │\n", | |
| "│ 61 │ \"go\" │ \"rand_mat_stat\" │ 8.92385 │ \"c\" │ 11.9548 │\n", | |
| "│ 62 │ \"java\" │ \"rand_mat_stat\" │ 4.00685 │ \"c\" │ 11.9548 │\n", | |
| "│ 63 │ \"javascript\" │ \"rand_mat_stat\" │ 3.32085 │ \"c\" │ 11.9548 │\n", | |
| "│ 64 │ \"julia\" │ \"rand_mat_stat\" │ 2.14423 │ \"c\" │ 11.9548 │\n", | |
| "│ 65 │ \"lua\" │ \"rand_mat_stat\" │ 4.33584 │ \"c\" │ 11.9548 │\n", | |
| "│ 66 │ \"mathematica\" │ \"rand_mat_stat\" │ 6.70853 │ \"c\" │ 11.9548 │\n", | |
| "│ 67 │ \"matlab\" │ \"rand_mat_stat\" │ 10.4784 │ \"c\" │ 11.9548 │\n", | |
| "│ 68 │ \"octave\" │ \"rand_mat_stat\" │ 35.919 │ \"c\" │ 11.9548 │\n", | |
| "│ 69 │ \"python\" │ \"rand_mat_stat\" │ 19.0412 │ \"c\" │ 11.9548 │\n", | |
| "│ 70 │ \"r\" │ \"rand_mat_stat\" │ 16.6461 │ \"c\" │ 11.9548 │" | |
| ] | |
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| "execution_count": 86, | |
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| " <clipPath id=\"img-f8dcd7ba-23\">\n", | |
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| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "p = plot(benchmarks,\n", | |
| " x = :language,\n", | |
| " y = :time,\n", | |
| " color = :benchmark,\n", | |
| " Scale.y_log10,\n", | |
| " Guide.ylabel(nothing),\n", | |
| " Guide.xlabel(nothing),\n", | |
| " Theme(\n", | |
| " default_point_size = 1mm,\n", | |
| " guide_title_position = :left,\n", | |
| " colorkey_swatch_shape = :circle,\n", | |
| " minor_label_font = \"Georgia\",\n", | |
| " major_label_font = \"Georgia\",\n", | |
| " ),\n", | |
| ")\n", | |
| "draw(SVG(8inch,8inch/golden), p)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 87, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "\n", | |
| "WARNING: deprecated syntax \"AbstractVecOrMat{T} (\" at /Users/sklee/.julia/v0.4/Winston/src/Winston.jl:96.\n", | |
| "Use \"AbstractVecOrMat{T}(\" instead.\n", | |
| "WARNING: requiring \"Dates\" in module \"Winston\" did not define a corresponding module.\n", | |
| "WARNING: module Winston should explicitly import * from Base\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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", | |
| "text/plain": [ | |
| "Winston.FramedPlot(...)" | |
| ] | |
| }, | |
| "execution_count": 87, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# Pkg.add(\"Winston\")\n", | |
| "import Winston # Matlab style plotting\n", | |
| "# Winston.figure(width=600, height=400)\n", | |
| "\n", | |
| "x = collect(-2pi:.01:2pi)\n", | |
| "pl = Winston.plot(x, cos(x))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 88, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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", | |
| "text/plain": [ | |
| "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x322c212d0>)" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| }, | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "PyObject <matplotlib.text.Text object at 0x3230ec690>" | |
| ] | |
| }, | |
| "execution_count": 88, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "import PyPlot # Julia interface to Matplotlib, a powerful python plotting library\n", | |
| "\n", | |
| "x = linspace(0,2*pi,1000); y = sin(3*x + 4*cos(2*x));\n", | |
| "PyPlot.plot(x, y, color=\"red\", linewidth=2.0, linestyle=\"--\")\n", | |
| "PyPlot.title(\"A sinusoidally modulated sinusoid\")\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Packages" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 101, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "916-element Array{AbstractString,1}:\n", | |
| " \"AbstractDomains\" \n", | |
| " \"Accumulo\" \n", | |
| " \"ActiveAppearanceModels\"\n", | |
| " \"Actors\" \n", | |
| " \"AffineTransforms\" \n", | |
| " \"AmplNLWriter\" \n", | |
| " \"Anasol\" \n", | |
| " \"AndorSIF\" \n", | |
| " \"AnsiColor\" \n", | |
| " \"AppConf\" \n", | |
| " \"AppleAccelerate\" \n", | |
| " \"ApproxFun\" \n", | |
| " \"Arbiter\" \n", | |
| " ⋮ \n", | |
| " \"XMLDict\" \n", | |
| " \"XSim\" \n", | |
| " \"XSV\" \n", | |
| " \"YAML\" \n", | |
| " \"Yelp\" \n", | |
| " \"Yeppp\" \n", | |
| " \"YT\" \n", | |
| " \"ZChop\" \n", | |
| " \"ZipFile\" \n", | |
| " \"Zlib\" \n", | |
| " \"ZMQ\" \n", | |
| " \"ZVSimulator\" " | |
| ] | |
| }, | |
| "execution_count": 101, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "Pkg.available()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 90, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "INFO: Nothing to be done\n", | |
| "INFO: METADATA is out-of-date — you may not have the latest version of Calculus\n", | |
| "INFO: Use `Pkg.update()` to get the latest versions of your packages\n", | |
| "INFO: Updating METADATA...\n", | |
| "INFO: Updating Plotly...\n", | |
| "INFO: Computing changes...\n", | |
| "INFO: No packages to install, update or remove\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "Pkg.add(\"Calculus\")\n", | |
| "Pkg.update()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 91, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "0.5403023058631036" | |
| ] | |
| }, | |
| "execution_count": 91, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "using Calculus\n", | |
| "\n", | |
| "derivative(x -> sin(x), 1.0)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 92, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "0.5403023058631036" | |
| ] | |
| }, | |
| "execution_count": 92, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "import Calculus\n", | |
| "\n", | |
| "Calculus.derivative(x -> sin(x), 1.0)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Image Plots\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 93, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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", | |
| "text/plain": [ | |
| "Gray Images.Image with:\n", | |
| " data: 500x500 Array{Float64,2}\n", | |
| " properties:\n", | |
| " timedim: 0\n", | |
| " colorspace: Gray\n", | |
| " colordim: 0\n", | |
| " spatialorder: y x\n", | |
| " pixelspacing: 1.0 1.0" | |
| ] | |
| }, | |
| "execution_count": 93, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "using Images\n", | |
| "using ImageMagick\n", | |
| "using QuartzImageIO\n", | |
| "\n", | |
| "const ϕ = golden\n", | |
| "\n", | |
| "function foo(z)\n", | |
| " c = (φ-2)+(φ-1)im\n", | |
| " max = 80\n", | |
| " for n = 1:max\n", | |
| " abs(z) ≥ 2 && return n-1\n", | |
| " z = z^2 + c\n", | |
| " end\n", | |
| " return max\n", | |
| "end\n", | |
| "\n", | |
| "foo(x, y) = foo(x + y*im)\n", | |
| "\n", | |
| "foo_grid(n) =\n", | |
| " broadcast(foo,\n", | |
| " linspace(-0.5, 1, n)',\n", | |
| " linspace(-1, 0.5, n))\n", | |
| "\n", | |
| "convert(Image, scale(foo_grid(500), 1/80))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Parallelization" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 94, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| " 1.029369 seconds (107.41 k allocations: 4.519 MB)\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "2500294072031143045" | |
| ] | |
| }, | |
| "execution_count": 94, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "nheads = @time @parallel (+) for i=1:100000000\n", | |
| " rand(Int)\n", | |
| "end" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Code Generation" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 95, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "\n", | |
| "define double @julia_f_25995(double) {\n", | |
| "top:\n", | |
| " %1 = fmul double %0, %0\n", | |
| " ret double %1\n", | |
| "}\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "f(x) = x*x\n", | |
| "\n", | |
| "code_llvm(f, (Float64,))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 96, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "\t.section\t__TEXT,__text,regular,pure_instructions\n", | |
| "Filename: In[95]\n", | |
| "Source line: 1\n", | |
| "\tpushq\t%rbp\n", | |
| "\tmovq\t%rsp, %rbp\n", | |
| "Source line: 1\n", | |
| "\tmulsd\t%xmm0, %xmm0\n", | |
| "\tpopq\t%rbp\n", | |
| "\tret\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "code_native(f, (Float64,))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Noteworthy Differences from other Languages \n", | |
| "\n", | |
| "(http://docs.julialang.org/en/release-0.4/manual/noteworthy-differences/)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "# This is a very brief intro to Julia. Learn more from http://julialang.org/learning/\n", | |
| "\n", | |
| "\n", | |
| "# Possible topics for student Julia presentation (bonus points)\n", | |
| "\n", | |
| " * Data structure and algorithms\n", | |
| " * Plotting (PyPlot and/or Gadfly)\n", | |
| " * Parallelization\n", | |
| " * DataFrame and operations for statistics" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Julia 0.4.5", | |
| "language": "julia", | |
| "name": "julia-0.4" | |
| }, | |
| "language_info": { | |
| "file_extension": ".jl", | |
| "mimetype": "application/julia", | |
| "name": "julia", | |
| "version": "0.4.5" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 0 | |
| } |
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