from scipy2018 import PySAL==2.0rc2

Returning from scipy 2018

My wrap-up from an exciting week full of stories about code and community at scipy 2018. First: I am even more convinced to keep on working on open source software in a fantastic community where scipy conference t-shirts are worn somewhat similar to festival t-shirts. Second: I was very impressed by the amount of new ideas, creative solutions and jokes (reference to the ‘catterplot’ and all lightning-talks) to encounter at the conference. Lastly, Dani asked me during the end of the sprints, “What changed your life this week?” – “Of course meeting the pysal team, my mentors and experiencing the spirit of coding together to finish the release of splot!”

I also had the change to introduce splot to the broader python community in a lightning talk, which you can see if you follow the link.

First splot release

This big announcement this week is that we successfully preliminary released splot as part of PySAL 2.0rc2.

You can install and access splot via PySAL 2.0:

pip install PySAL==2.0rc2
You can download PySAL-2.0 file from pypi.org. Release notes and some statistics about PySAL - 2.0 can be accessed here. More information about migrating to PySAL 2.0 can be found here. And our brand new team website which can be accessed here (which is partly still in the making).

Extended functionality

Next to these exciting news, I have continued extending and fine-tuning splot‘s functionality to make it more user friendly. For example, you can now use splot.esda.moran_scatterplot() to plot all esda.moranobjects, instead of calling functions specific to Moran, Moran_Local, Moran_BV, ….
from splot.esda import moran_scatterplot

fig, axs = plt.subplots(2, 2, figsize=(10,10),
                        subplot_kw={'aspect': 'equal'})

moran_scatterplot(moran, p=0.05, ax=axs[0,0])
moran_scatterplot(moran_loc, p=0.05, ax=axs[1,0])
moran_scatterplot(moran_bv, p=0.05, ax=axs[0,1])
moran_scatterplot(moran_loc_bv, p=0.05, ax=axs[1,1])
plt.show()
 
Furthermore, I implemented moran_facet() which allows to plot moran statistics calculated for a variety of attributes:
from splot.esda import moran_facet

fig, axarr = moran_facet(moran_matrix)
plt.show()

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