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Merge pull request #152 from Carreau/cleanup
cleanup nbviewer frontpage
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[ | ||
{ | ||
"header":"Programming Languages", | ||
"links":[ | ||
{ | ||
"text": "IPython Examples", | ||
"target": "github/ipython/ipython/tree/master/examples/notebooks", | ||
"img": "/static/img/example-nb/ipython-thumb.png" | ||
}, | ||
{ | ||
"text": "IRuby Notebook", | ||
"target": "github/minad/iruby/blob/master/IRuby-Example.ipynb", | ||
"img": "/static/img/example-nb/iruby-nb.png" | ||
}, | ||
{ | ||
"text": "An IJulia Preview", | ||
"target": "url/jdj.mit.edu/~stevenj/IJulia%20Preview.ipynb", | ||
"img": "/static/img/example-nb/ijulia-preview.png" | ||
} | ||
] | ||
}, | ||
{ | ||
"header":"Books", | ||
"links":[ | ||
{ | ||
"text": "Python for Signal Processing", | ||
"target": "http://nbviewer.ipython.org/github/unpingco/Python-for-Signal-Processing/", | ||
"img": "/static/img/example-nb/python-signal.png" | ||
}, | ||
{ | ||
"text": "O'Reilly Book", | ||
"target": "github/ptwobrussell/Mining-the-Social-Web-2nd-Edition/tree/master/ipynb", | ||
"img": "/static/img/example-nb/mining-slice.png" | ||
}, | ||
{ | ||
"text": "Probabilistic Programming", | ||
"target": "github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/blob/master/Chapter1_Introduction/Chapter1_Introduction.ipynb", | ||
"img": "/static/img/example-nb/probabilistic-bayesian.png" | ||
} | ||
] | ||
}, | ||
{ | ||
"header":"Misc", | ||
"links":[ | ||
{ | ||
"text": "Interactive plots with Plotly", | ||
"target": "github/plotly/IPython-plotly/tree/master/", | ||
"img": "/static/img/example-nb/plotly.png" | ||
}, | ||
{ | ||
"text": "XKCD Plot With Matplotlib", | ||
"target": "url/jakevdp.github.com/downloads/notebooks/XKCD_plots.ipynb", | ||
"img": "/static/img/example-nb/XKCD-Matplotlib.png" | ||
}, | ||
{ | ||
"text": "Non Parametric Regression", | ||
"target": "gist/fonnesbeck/2352771", | ||
"img": "/static/img/example-nb/covariance.png" | ||
}, | ||
{ | ||
"text": "Exploring R formula", | ||
"target": "github/fperez/nipy-notebooks/blob/master/exploring_r_formula.ipynb", | ||
"img": "/static/img/example-nb/exploring_r_formula.png" | ||
}, | ||
{ | ||
"text": "Nose testing", | ||
"target": "github/swcarpentry/2012-11-scripps/blob/master/python/testing-with-nose.ipynb", | ||
"img": "/static/img/example-nb/nose_testing.png" | ||
}, | ||
{ | ||
"text": "Working with pandas", | ||
"target": "gist/twiecki/3962843", | ||
"img": "/static/img/example-nb/working_with_pandas.png" | ||
}, | ||
{ | ||
"text": "Fitting", | ||
"target": "gist/keflavich/4042018", | ||
"img": "/static/img/example-nb/fitting.png" | ||
}, | ||
{ | ||
"text": "Analysis of current events", | ||
"target": "gist/darribas/4121857", | ||
"img": "/static/img/example-nb/gaza.png" | ||
}, | ||
{ | ||
"text": "Jaynes-Cummings model", | ||
"target": "github/jrjohansson/qutip-lectures/blob/master/Lecture-1-Jaynes-Cumming-model.ipynb", | ||
"img": "/static/img/example-nb/jaynes-cummings.png" | ||
}, | ||
{ | ||
"text": "SymPy notebook", | ||
"target": "github/ipython/ipython/blob/master/examples/notebooks/SymPy Examples.ipynb", | ||
"img": "/static/img/example-nb/sympy.png" | ||
}, | ||
{ | ||
"text": "Numpy tests", | ||
"target": "gist/Juanlu001/3914904", | ||
"img": "/static/img/example-nb/numpy_tests.png" | ||
}, | ||
{ | ||
"text": "R magic extension", | ||
"target": "github/ipython/ipython/blob/master/examples/notebooks/R Magics.ipynb", | ||
"img": "/static/img/example-nb/r_magic.png" | ||
} | ||
] | ||
} | ||
] |
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# Images for frontpage | ||
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This contain images for the frontpage of nbviewer. | ||
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at most thoses images will be show with a size of 360x225 (W x H), aspect ratio | ||
(W/H) of 1.6. As they might be show on retina display, consider using a double | ||
resolution. Resizing will be handled by browser, so to avoid artifact images | ||
shoudl be of size multiple of maximum size ie (720 width) by (450 height), | ||
preferentially in png, and passed to png crusher as the number of request for | ||
thoses images will be heigh. | ||
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