test_display.ipynb
336 lines
| 84.4 KiB
| text/plain
|
TextLexer
Jonathan Taylor
|
r7372 | { | |
"metadata": { | |||
"name": "Test_notebook" | |||
}, | |||
"nbformat": 3, | |||
"worksheets": [ | |||
{ | |||
"cells": [ | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"from IPython.core.displaypub import publish_display_data", | |||
"%load_ext rmagic", | |||
"", | |||
"publish_display_data('Assignment1', {'text/html':'<h2>Question 1</h2>'})" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"html": [ | |||
"<h2>Question 1</h2>" | |||
], | |||
"output_type": "display_data" | |||
} | |||
], | |||
"prompt_number": 3 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"%%R ", | |||
"X = rnorm(40)", | |||
"Y = rnorm(40)", | |||
"plot(X,Y, pch=24, bg='red', cex=2)" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "display_data", | |||
"png": 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o1KiR3vk9Zs7E17EJaHvHtmRoWQWs1/px20EA9BRwfHw8Xn75ZaxevRrvv/++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\nIMAAABggwAAAGPgL1j9zECZdsN4AAAAASUVORK5CYII=\n" | |||
} | |||
], | |||
"prompt_number": 4 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"publish_display_data('Assignment1',{'text/latex':r'''What is the correlation, $\\rho$? We could also have plotted with matplotlib...'''})", | |||
"" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"latex": [ | |||
"What is the correlation, $\\rho$? We could also have plotted with matplotlib..." | |||
], | |||
"output_type": "display_data" | |||
} | |||
], | |||
"prompt_number": 5 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"import pylab", | |||
"%Rpull X Y", | |||
"pylab.scatter(X, Y, c='r')", | |||
"pylab.gca().set_xlabel('X')", | |||
"pylab.gca().set_ylabel('Y')" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "pyout", | |||
"prompt_number": 6, | |||
"text": [ | |||
"<matplotlib.text.Text at 0xba0dfd0>" | |||
] | |||
} | |||
], | |||
"prompt_number": 6 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"publish_display_data('Assignment1',{'text/html':r'''We might include some other html stuff, too. ", | |||
"", | |||
"<iframe width=\"560\" height=\"315\" src=\"http://www.youtube.com/embed/sf49cw0134U\" ", | |||
"frameborder=\"0\" allowfullscreen></iframe>'''})" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"html": [ | |||
"We might include some other html stuff, too. ", | |||
"", | |||
"<iframe width=\"560\" height=\"315\" src=\"http://www.youtube.com/embed/sf49cw0134U\" ", | |||
"frameborder=\"0\" allowfullscreen></iframe>" | |||
], | |||
"output_type": "display_data" | |||
} | |||
], | |||
"prompt_number": 7 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"", | |||
"publish_display_data('Assignment1',{'text/html':'<h2>Answer</h2>'})" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"html": [ | |||
"<h2>Answer</h2>" | |||
], | |||
"output_type": "display_data" | |||
} | |||
], | |||
"prompt_number": 8 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"publish_display_data('Assignment', {'text/html': '''<input type=\"radio\" name=\"group1\" value=\"Milk\"> Milk<br>", | |||
"<input type=\"radio\" name=\"group1\" value=\"Butter\" checked> Butter<br>'''})", | |||
"" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"html": [ | |||
"<input type=\"radio\" name=\"group1\" value=\"Milk\"> Milk<br>", | |||
"<input type=\"radio\" name=\"group1\" value=\"Butter\" checked> Butter<br>" | |||
], | |||
"output_type": "display_data" | |||
} | |||
], | |||
"prompt_number": 9 | |||
}, | |||
{ | |||
"cell_type": "heading", | |||
"level": 2, | |||
"source": [ | |||
"Magics", | |||
"" | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"run magics/homework.py" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 10 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"%%MultipleChoiceSetup 1", | |||
"", | |||
"X = rnorm(200)", | |||
"Y = rnorm(200)", | |||
"plot(X,Y)" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"html": [ | |||
"<h2>Question 1</h2>" | |||
], | |||
"output_type": "display_data" | |||
}, | |||
{ | |||
"output_type": "display_data", | |||
"png": 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HL/UxZMgQREZGolOnTli7di2ePXuGlJQUHDt2DAcOHICtrS2cnZ0hLCwMMzMz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\nK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| |||
} | |||
], | |||
"prompt_number": 11 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"%%MultipleChoiceQuestion 1", | |||
"", | |||
"question_text = 'Is the correlation:'", | |||
"choices = ['positive', 'negative', 'zero']" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"latex": [ | |||
"Is the correlation:" | |||
], | |||
"output_type": "display_data" | |||
}, | |||
{ | |||
"html": [ | |||
"", | |||
" <input type=\"radio\" name=\"2917924107d1f41e90632af0a98a4793\" value=\"zero\"> zero<br>", | |||
" ", | |||
"", | |||
" <input type=\"radio\" name=\"2917924107d1f41e90632af0a98a4793\" value=\"negative\"> negative<br>", | |||
" ", | |||
"", | |||
" <input type=\"radio\" name=\"2917924107d1f41e90632af0a98a4793\" value=\"positive\"> positive<br>", | |||
" " | |||
], | |||
"output_type": "display_data" | |||
} | |||
], | |||
"prompt_number": 12 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"%%MultipleChoiceSetup 2", | |||
"", | |||
"X = rnorm(20)", | |||
"Y = rnorm(20) + Y", | |||
"print(summary(lm(Y~X)))", | |||
"", | |||
"true_corr = cor(X,Y)" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"html": [ | |||
"<h2>Question 2</h2>" | |||
], | |||
"output_type": "display_data" | |||
}, | |||
{ | |||
"output_type": "display_data", | |||
"text": [ | |||
"", | |||
"Call:", | |||
"lm(formula = Y ~ X)", | |||
"", | |||
"Residuals:", | |||
" Min 1Q Median 3Q Max ", | |||
"-1.9189 -0.9845 -0.5326 1.1005 2.5939 ", | |||
"", | |||
"Coefficients:", | |||
" Estimate Std. Error t value Pr(>|t|)", | |||
"(Intercept) 0.3573 0.3301 1.082 0.293", | |||
"X 0.5617 0.4137 1.358 0.191", | |||
"", | |||
"Residual standard error: 1.445 on 18 degrees of freedom", | |||
"Multiple R-squared: 0.09288,\tAdjusted R-squared: 0.04248 ", | |||
"F-statistic: 1.843 on 1 and 18 DF, p-value: 0.1914 ", | |||
"", | |||
"" | |||
] | |||
} | |||
], | |||
"prompt_number": 23 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"true_corr = %R cor(X,Y)" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 24 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"%%MultipleChoiceQuestion 2", | |||
"", | |||
"question_text = r'Up to 1 significant digit, what is the correlation between $X$ and $Y$?'", | |||
"", | |||
"while True:", | |||
" choices = ['%0.1f' % c for c in list(np.random.random(size=(3,))*2-1) + [true_corr]]", | |||
" if len(set(choices)) == 4 :", | |||
" break", | |||
"", | |||
"" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"latex": [ | |||
"Up to 1 significant digit, what is the correlation between $X$ and $Y$?" | |||
], | |||
"output_type": "display_data" | |||
}, | |||
{ | |||
"html": [ | |||
"", | |||
" <input type=\"radio\" name=\"96eedd18fc3bbd5cef5164686e0dce1a\" value=\"0.1\"> 0.1<br>", | |||
" ", | |||
"", | |||
" <input type=\"radio\" name=\"96eedd18fc3bbd5cef5164686e0dce1a\" value=\"-0.8\"> -0.8<br>", | |||
" ", | |||
"", | |||
" <input type=\"radio\" name=\"96eedd18fc3bbd5cef5164686e0dce1a\" value=\"0.3\"> 0.3<br>", | |||
" ", | |||
"", | |||
" <input type=\"radio\" name=\"96eedd18fc3bbd5cef5164686e0dce1a\" value=\"-0.2\"> -0.2<br>", | |||
" " | |||
], | |||
"output_type": "display_data" | |||
} | |||
], | |||
"prompt_number": 27 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 14 | |||
} | |||
] | |||
} | |||
] | |||
} |