Idea Collection: Functionality to support in splot
slumnitz opened this issue · 1 comments
Space to collect ideas which functionality to support for each sub package in splot
esda
- Choropleth functionality for each algorithm in esda.mapclassify.
- Spatial Autocorrelation:
- Global Moran scatter plot (Moran_Scatterplot())
- Global Moran Bivariate scatter plot (Moran_BV_Scatterplot())
- Global Moran Bivariate scatter plot facetting matrix (Moran_BV_facet())
- Global Moran Rate scatter plot (Moran_Rate_Scatterplot())
- Local Moran map (Moran_Local_Map())
- Local Moran Bivariate map (Moran_Local_BV_Map())
- Local Moran Rate map (Moran_Local_Rate_Map())
- Local Getis-Ord map (G_Local_Map())
giddy
- dynamic LISA
- dynamic LISA heatmap (dynamic_lisa_heatmap(rose))
- dynamic LISA rose diagrams (dynamic_lisa_rose(rose))
- dynamic LISA vectors (dynamic_lisa_vectors(rose))
- dynamic LISA composite plot (dynamic_lisa_composite(rose, gdf))
- dynamic LISA interactive composite plot (dynamic_lisa_composite_explore(rose, gdf))
- LIMA
spreg
splot.vba
- value by alpha maps: http://andywoodruff.com/blog/value-by-alpha-maps/
- change RGB -> alpha, plug to mpl (Paper)
core splot
- BV and TriV choropleths
- BV LISA matrix
- Triangles for BiVAriate choropleths
- conditional map
- facets (prototype example)
I am playing with different visualisations for all esda.moran
objects at the moment. The moran_loc_scatterplot()
so far displays standardised attribute values and corresponding spatial lag values (Moran_loc.z
). I was wondering if it would make sense to also give an option ((standardized=False,...)
) for non-standardised values in the scatterplot, displaying the actual attribute values and their spatial lag. I am not sure if this would be of use?
I would like to try and implement this scatterplot blueprint (+ additional visualizations) for all esda.moran
objects (Moran_Local
, Moran
, Moran_BV
,...) in the next two weeks. If I implement standardised values for all scatterplots, does Moran_BV
also have an .z
argument or something similar?
What do you think @sjsrey @TaylorOshan @darribas @ljwolf