API reference¶
splot.giddy
¶
Provides visualisations for the Geospatial Distribution Dynamics - giddy module. giddy provides a tool for space–time analytics that consider the role of space in the evolution of distributions over time.
Directional LISA analytics¶
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Heatmap indicating significant transition of LISA values over time inbetween Moran Scatterplot quadrants |
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Plot dynamic LISA values in a rose diagram. |
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Plot vectors of positional transition of LISA values in Moran scatterplot |
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Composite visualisation for dynamic LISA values over two points in time. |
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Interactive exploration of dynamic LISA values for different dates in a dataframe. |
splot.esda
¶
Provides visualisations for the esda subpackage. esda provides tools for exploratory spatial data analysis that consider the role of space in a distribution of attribute values.
Moran analytics¶
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Moran Scatterplot |
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Global Moran’s I simulated reference distribution. |
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Global Moran’s I simulated reference distribution and scatterplot. |
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Bivariate Moran’s I simulated reference distribution. |
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Bivariate Moran’s I simulated reference distribution and scatterplot. |
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Create a LISA Cluster map |
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Produce three-plot visualisation of Moran Scatteprlot, LISA cluster and Choropleth maps, with Local Moran region and quadrant masking |
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Moran Facet visualization. |
splot.libpysal
¶
Provides visualisations for all core components of Python Spatial Analysis Library in libpysal.
libpysal weights¶
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Plot spatial weights network. |
splot.mapping
¶
Provides Choropleth visualizations and mapping utilities.
Value-by-Alpha maps¶
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Calculates Value by Alpha rgba values |
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Value by Alpha Choropleth |
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Creates Value by Alpha heatmap used as choropleth legend. |
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Classify your data with pysal.mapclassify Note: Input parameters are dependent on classifier used. |
Colormap utilities¶
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Function to offset the “center” of a colormap. |
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Function to truncate a colormap by selecting a subset of the original colormap’s values |