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Exploration of potential interfaces for alternative packages #22
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Hi Stefanie! I was trying to develop some plotly's functions based on the splot native functions. I think I managed to develop the scatterplot offline for either in the terminal and for jupyter notebooks. Did you work on some of your ideas of this issue? I've heard that there's some interactivity already implemented in splot, but I couldn't find yet. An example of a plotly scatterplot function would be:
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Answering the question how and which interactive package to integrate or not to integrate into
splot
Idea and Experiment collection in order to decide on:
splot
andPySAL
functionality could/ should be supported interactively in futureTo get a clear idea on what is possible and how a future integration could look like, I suggest to undertake experiments designing API's and assessing what is possible with alternative packages.
I will therefore test different packages generating the
esda.moran.Moran_Local
(scatterplot, LISA map, Choropleth map) andgiddy.directional
(heatmap, LISA maps, rose plot))visualisation.
I am aiming for an API design that is as close as possible to the
matplotlib
API. This will help to provide an insight into whether or not it is viable to use aset_backend('package')
option, to quickly change backend packages or not.I am testing under the assumption that interactive backends are used for the exploration of data and statistical results, not necessarily for publishing in a paper (we have the
matplotlib
interface for this). Therefore I will limit the options to customise visualisations to a minimum. I would suggest to ideally make the interactive backend a default or if not possible provide an additional method for PySAL objects.plot_interactive()
, since interactive plotting could provide an attractive alternative to interfaces commonly used in the geographic sphere (software packages like GRASS, ArcMaps...).Interactive visualisation packages:
JavaScript
based and I am not familiar withJavaScript
)Testing criteria:
matplotlib
API (without too much effort)?Possible outcomes:
matplotlib
functionality (widgets, masking options, ...)set_backend('bk')
optionResults
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