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1d
comment Visually summarising multiple diverse metric results
Ah, ok. Not used to "standardise" used in that way :)
2d
comment Partial compile latex and bibtex for pandoc
Can you add what you've already tried? pandoc blah.md -o blah.doc --bibliography=citations.bib works fine for me for the bibiliography. Images don't seem to work though.
2d
comment Visually summarising multiple diverse metric results
Those plots only show one type of value over a grid. The problem is that the metric/variable combinations produce random variables that have vastly different distributions, so you won't get anything like the smoothness or comparability as you do with those plots. But yeah, so far barplots is about the the best option I can see (perhaps minmax or mean/variance normalised over models).
2d
revised Visually summarising multiple diverse metric results
clarify metrics
Aug
31
comment Visually summarising multiple diverse metric results
Fair point about visualisation maybe not being suitable, I though as much, but thought I'd check first. Tree maps are an interesting idea, but I'm focussing more on trying to summarise across metrics than across variables, so I'd need more than two variables.
Aug
28
comment Can we interact with the new Wikipedia WikiProject: Earth Sciences?
I guess I was imagining that by reducing duplication, work would be reduced. But I don't have a solid plan, which is why I was asking for ideas here.
Aug
28
comment Can colorized output be captured via shell redirect?
There's a script called ansi2html that does an OK job of converting the resulting typescript to HTML.
Aug
28
comment Can we interact with the new Wikipedia WikiProject: Earth Sciences?
How do you mean "sustainable"? I wasn't thinking that they'd try to fulfil the same role, that would be pointless. I was thinking that they'd be complementary . e.g. ES.SE already as a policy to close questions that can be answered easily by reading the relevant wikipedia page, and ES.SE questions could help identify important missing components in Wikipedia's Earth Science coverage.
Aug
27
comment Link to class method in python docstring
You can do it with the :any: role - see the note about default_setting.
Aug
25
asked Visually summarising multiple diverse metric results
Aug
25
comment What is the difference between pip and conda?
Also, it's really easy to install any python package (that uses setuptools) from source in conda. Just create a recipe, and conda build, and it will create a re-usable package that you can share with others via binstar or similar.
Aug
25
comment What is the difference between pip and conda?
For an idea of the kind of things you can use conda to handle, checkout out github.com/conda/conda-recipes. Also, this answer leaves out the fact that conda is an environment manager as well, whereas with pip you have to fall back to something horrible like virtualenv.
Aug
25
comment What is the difference between pip and conda?
@Matt: IPython, not IPyhton.
Aug
25
asked Can we interact with the new Wikipedia WikiProject: Earth Sciences?
Aug
25
comment Is there a way to create interactive plots (a la D3) in IPython notebooks?
+1 mpld3 is pretty sweet. You can just import it, and run mpld3.enable_notebook() below your %pylab inline call, and all plots become interactive. Can get a bit slow though.
Aug
25
comment ipython server can't launch: No module named notebook.notebookapp
Given that @AndySmith's answer is generally more applicable and correct from now on, you should probably make it explicit that this isn't the recommended solution for the general problem, or just delete this answer.
Aug
25
comment ipython server can't launch: No module named notebook.notebookapp
Please select @AndySmith's answer, so it floats to the top, as it is more correct.
Aug
22
awarded Necromancer
Aug
21
comment Iterate over nested dictionary
@theta: works fine, for one interpretation of your question. If you want it to loop through lists as well, add an elif isinstance([], (list, tuple)): and then for v in d: recurse(v).
Aug
21
comment Implementing horizon charts in matplotlib
There's something wrong with this implementation. Try y = np.array([0,100,-100,100,0]).T ; horizonPlot(range(5), y) - the problem is that you have to add an x value between every pair of y values that crosses an axis.
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